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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "af034c62",
+   "metadata": {},
+   "source": [
+    "## hyperactive - unified interfaces for optimizers and experiments"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "830f7eb7",
+   "metadata": {},
+   "source": [
+    "### \"experiment\" = optimization problem"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "668f9ccc",
+   "metadata": {},
+   "source": [
+    "\"experiment\" classes model optimization functions and ML experiments under one API\n",
+    "\n",
+    "Examples below:\n",
+    "1. simple objective function - parabola function\n",
+    "2. ML cross-validation experiment in sklearn"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2380a84b",
+   "metadata": {},
+   "source": [
+    "#### user defined objective function"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "21f50e9e",
+   "metadata": {},
+   "source": [
+    "simple objective definition:\n",
+    "\n",
+    "* function with single dict argument\n",
+    "* keys are variable names\n",
+    "* function evaluates variables and returns float\n",
+    "* maximization is assumed later"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "8c428229",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sphere(opt):\n",
+    "    x = opt[\"x\"]\n",
+    "    y = opt[\"y\"]\n",
+    "\n",
+    "    return -x**2 - y**2"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a242a2fc",
+   "metadata": {},
+   "source": [
+    "to evaluate:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "ccb460f1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "-13"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sphere({\"x\": 2, \"y\": 3})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "173f1923",
+   "metadata": {},
+   "source": [
+    "#### parametric objective functions - parametric"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fd01be6c",
+   "metadata": {},
+   "source": [
+    "parametric objective functions are classes:\n",
+    "\n",
+    "* construct with parameters\n",
+    "* call `evaluate` with `dict`\n",
+    "\n",
+    "`hyperactive` comes with predefined objective functions.\n",
+    "\n",
+    "These are parametric through the constructor\n",
+    "\n",
+    "Example: `Parabola` function, docstring outlines parametric form"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "c474de73",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1;31mInit signature:\u001b[0m \u001b[0mParabola\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m1.0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mb\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;31mDocstring:\u001b[0m      Parabola class.\n",
+      "\u001b[1;31mInit docstring:\u001b[0m Construct BaseObject.\n",
+      "\u001b[1;31mFile:\u001b[0m           c:\\workspace\\hyperactive\\src\\hyperactive\\experiment\\bench\\_parabola.py\n",
+      "\u001b[1;31mType:\u001b[0m           type\n",
+      "\u001b[1;31mSubclasses:\u001b[0m     "
+     ]
+    }
+   ],
+   "source": [
+    "from hyperactive.experiment.bench import Parabola\n",
+    "\n",
+    "?Parabola"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "59dd4715",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "parabola = Parabola(a=42, b=3, c=4)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1de4894a",
+   "metadata": {},
+   "source": [
+    "parametric objectives are evaluated via `evaluate` method:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "97b41711",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "np.float64(564.0)"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "score, metadata = parabola.evaluate({\"x\": 2, \"y\": 3})  # also returns metadata\n",
+    "score"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4f561158",
+   "metadata": {},
+   "source": [
+    "instances of parametric objectives are also directly callable"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "797535db",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "np.float64(-564.0)"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "parabola(x=2, y=3)\n",
+    "# output is always np.float64"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b8096712",
+   "metadata": {},
+   "source": [
+    "the \"experiment\" class has two sets of variables:\n",
+    "\n",
+    "* optimization variables = inputs of the objective - inspectable via `paramnames`\n",
+    "* parameters of the experiment = constant in the objective\n",
+    "    * these are params of `__init__`\n",
+    "    * and are inspectable via `get_params`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "fc08e901",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['x', 'y']"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "parabola.paramnames()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "61a62efa",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['a', 'b', 'c']"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "list(parabola.get_params())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a1dbc553",
+   "metadata": {},
+   "source": [
+    "call via `score` method:\n",
+    "\n",
+    "* returns two objects: the value, and metadata (in a dict)\n",
+    "* input is a single dict, the `**` variant of a direct call"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "b127d406",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(np.float64(-564.0), {})"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "parabola.score({\"x\": 2, \"y\": 3})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "98924abf",
+   "metadata": {},
+   "source": [
+    "#### sklearn cross-validation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a625210e",
+   "metadata": {},
+   "source": [
+    "\"experiment\" can be more complicated - e.g., a cross-validation experiment\n",
+    "\n",
+    "this is a single tuning-evaluation step for an `sklearn` estimator"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "57110e86",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from hyperactive.experiment.integrations import SklearnCvExperiment\n",
+    "from sklearn.datasets import load_iris\n",
+    "from sklearn.svm import SVC\n",
+    "from sklearn.metrics import accuracy_score\n",
+    "from sklearn.model_selection import KFold\n",
+    "\n",
+    "X, y = load_iris(return_X_y=True)\n",
+    "\n",
+    "sklearn_exp = SklearnCvExperiment(\n",
+    "    estimator=SVC(),\n",
+    "    scoring=accuracy_score,\n",
+    "    cv=KFold(n_splits=3, shuffle=True),\n",
+    "    X=X,\n",
+    "    y=y,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "dcf183ae",
+   "metadata": {},
+   "source": [
+    "usage syntax same as for the simple parabola!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "70a27348",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "np.float64(0.9733333333333333)"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sklearn_exp(C=1, gamma=0.3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "1cfd28d4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['C',\n",
+       " 'break_ties',\n",
+       " 'cache_size',\n",
+       " 'class_weight',\n",
+       " 'coef0',\n",
+       " 'decision_function_shape',\n",
+       " 'degree',\n",
+       " 'gamma',\n",
+       " 'kernel',\n",
+       " 'max_iter',\n",
+       " 'probability',\n",
+       " 'random_state',\n",
+       " 'shrinking',\n",
+       " 'tol',\n",
+       " 'verbose']"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sklearn_exp.paramnames()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "165c5830",
+   "metadata": {},
+   "source": [
+    "`get_params` works like in `sklearn` and is nested\n",
+    "\n",
+    "note that similar parameters appear as in `paramnames`\n",
+    "\n",
+    "* parameters in `paramnames` are optimized over\n",
+    "* parameters in `get_params` are default values, if not set in `score`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "b6160e3c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['X',\n",
+       " 'cv',\n",
+       " 'estimator',\n",
+       " 'scoring',\n",
+       " 'y',\n",
+       " 'estimator__C',\n",
+       " 'estimator__break_ties',\n",
+       " 'estimator__cache_size',\n",
+       " 'estimator__class_weight',\n",
+       " 'estimator__coef0',\n",
+       " 'estimator__decision_function_shape',\n",
+       " 'estimator__degree',\n",
+       " 'estimator__gamma',\n",
+       " 'estimator__kernel',\n",
+       " 'estimator__max_iter',\n",
+       " 'estimator__probability',\n",
+       " 'estimator__random_state',\n",
+       " 'estimator__shrinking',\n",
+       " 'estimator__tol',\n",
+       " 'estimator__verbose']"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "list(sklearn_exp.get_params().keys())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "f74ca927",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(np.float64(0.98),\n",
+       " {'score_time': array([0.        , 0.01113176, 0.00051761]),\n",
+       "  'fit_time': array([0.        , 0.        , 0.00100803]),\n",
+       "  'n_test_samples': 150})"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sklearn_exp.score({\"C\": 1, \"gamma\": 0.3})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "71073496",
+   "metadata": {},
+   "source": [
+    "### use of optimizers"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "725230fc",
+   "metadata": {},
+   "source": [
+    "#### optimizing a custom objective"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "ab78b796",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sphere(opt):\n",
+    "    x = opt[\"x\"]\n",
+    "    y = opt[\"y\"]\n",
+    "\n",
+    "    return -x**2 - y**2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "7104e5ec",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "                                                                                                                       \r"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "{'x': np.float64(0.10101010101010033), 'y': np.float64(0.10101010101010033)}"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "from hyperactive.opt import HillClimbing\n",
+    "\n",
+    "hillclimbing_config = {\n",
+    "    \"search_space\": {\n",
+    "        \"x\": np.linspace(-10, 10, 100),\n",
+    "        \"y\": np.linspace(-10, 10, 100),\n",
+    "    },\n",
+    "    \"n_iter\": 1000,\n",
+    "}\n",
+    "hill_climbing = HillClimbing(**hillclimbing_config, experiment=sphere)\n",
+    "\n",
+    "hill_climbing.solve()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "300a1666",
+   "metadata": {},
+   "source": [
+    "#### Grid search & sklearn CV"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "5e2328c9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from hyperactive.experiment.integrations import SklearnCvExperiment\n",
+    "from sklearn.datasets import load_iris\n",
+    "from sklearn.svm import SVC\n",
+    "from sklearn.metrics import accuracy_score\n",
+    "from sklearn.model_selection import KFold\n",
+    "\n",
+    "X, y = load_iris(return_X_y=True)\n",
+    "\n",
+    "sklearn_exp = SklearnCvExperiment(\n",
+    "    estimator=SVC(),\n",
+    "    scoring=accuracy_score,\n",
+    "    cv=KFold(n_splits=3, shuffle=True),\n",
+    "    X=X,\n",
+    "    y=y,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "e9a07a73",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'C': 0.01, 'gamma': 1}"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from hyperactive.opt import GridSearchSk as GridSearch\n",
+    "\n",
+    "param_grid = {\n",
+    "    \"C\": [0.01, 0.1, 1, 10],\n",
+    "    \"gamma\": [0.0001, 0.01, 0.1, 1, 10],\n",
+    "}\n",
+    "grid_search = GridSearch(param_grid=param_grid, experiment=sklearn_exp)\n",
+    "\n",
+    "grid_search.solve()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "72fcf886",
+   "metadata": {},
+   "source": [
+    "#### hill climbing & sklearn CV"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "f9a4d922",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from hyperactive.experiment.integrations import SklearnCvExperiment\n",
+    "from sklearn.datasets import load_iris\n",
+    "from sklearn.svm import SVC\n",
+    "from sklearn.metrics import accuracy_score\n",
+    "from sklearn.model_selection import KFold\n",
+    "\n",
+    "X, y = load_iris(return_X_y=True)\n",
+    "\n",
+    "sklearn_exp = SklearnCvExperiment(\n",
+    "    estimator=SVC(),\n",
+    "    scoring=accuracy_score,\n",
+    "    cv=KFold(n_splits=3, shuffle=True),\n",
+    "    X=X,\n",
+    "    y=y,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "9a13b4f3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "                                                                                                           \r"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "{'C': np.float64(10.0), 'gamma': np.float64(0.1)}"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "from hyperactive.opt import HillClimbing\n",
+    "\n",
+    "hillclimbing_config = {\n",
+    "    \"search_space\": {\n",
+    "    \"C\": np.array([0.01, 0.1, 1, 10]),\n",
+    "    \"gamma\": np.array([0.0001, 0.01, 0.1, 1, 10]),\n",
+    "    },\n",
+    "    \"n_iter\": 100,\n",
+    "}\n",
+    "hill_climbing = HillClimbing(**hillclimbing_config, experiment=sklearn_exp)\n",
+    "\n",
+    "hill_climbing.solve()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7a933b41",
+   "metadata": {},
+   "source": [
+    "### full sklearn integration as estimator"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1f368679",
+   "metadata": {},
+   "source": [
+    "`OptCV` allows `sklearn` tuning via any tuning algorithm.\n",
+    "\n",
+    "Below, we show tuning via:\n",
+    "\n",
+    "* standard `GridSearch`\n",
+    "* `HillClimbing` from `gradient-free-optimizers`"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7171fc17",
+   "metadata": {},
+   "source": [
+    "##### `OptCV` tuning via `GridSearch`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "4bdf2d49",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 1. defining the tuned estimator\n",
+    "from sklearn.svm import SVC\n",
+    "from hyperactive.integrations.sklearn import OptCV\n",
+    "from hyperactive.opt import GridSearchSk as GridSearch\n",
+    "\n",
+    "param_grid = {\"kernel\": [\"linear\", \"rbf\"], \"C\": [1, 10]}\n",
+    "tuned_svc = OptCV(SVC(), optimizer=GridSearch(param_grid))\n",
+    "\n",
+    "# 2. fitting the tuned estimator = tuning the hyperparameters\n",
+    "from sklearn.datasets import load_iris\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "\n",
+    "X, y = load_iris(return_X_y=True)\n",
+    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)\n",
+    "\n",
+    "tuned_svc.fit(X_train, y_train)\n",
+    "\n",
+    "# 3. making predictions with the tuned estimator\n",
+    "y_pred = tuned_svc.predict(X_test)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1a4bddc0",
+   "metadata": {},
+   "source": [
+    "best parameters and best estimator can be returned"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "fdd8c14a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "best_params = tuned_svc.best_params_"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "252efea6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-1 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --sklearn-color-text: black;\n",
+       "  --sklearn-color-line: gray;\n",
+       "  /* Definition of color scheme for unfitted estimators */\n",
+       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
+       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+       "  --sklearn-color-unfitted-level-3: chocolate;\n",
+       "  /* Definition of color scheme for fitted estimators */\n",
+       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
+       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
+       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
+       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
+       "\n",
+       "  /* Specific color for light theme */\n",
+       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-icon: #696969;\n",
+       "\n",
+       "  @media (prefers-color-scheme: dark) {\n",
+       "    /* Redefinition of color scheme for dark theme */\n",
+       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-icon: #878787;\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 input.sk-hidden--visually {\n",
+       "  border: 0;\n",
+       "  clip: rect(1px 1px 1px 1px);\n",
+       "  clip: rect(1px, 1px, 1px, 1px);\n",
+       "  height: 1px;\n",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
+       "  border: 1px dashed var(--sklearn-color-line);\n",
+       "  margin: 0 0.4em 0.5em 0.4em;\n",
+       "  box-sizing: border-box;\n",
+       "  padding-bottom: 0.4em;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-container {\n",
+       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+       "     so we also need the `!important` here to be able to override the\n",
+       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+       "  display: inline-block !important;\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-parallel-item,\n",
+       "div.sk-serial,\n",
+       "div.sk-item {\n",
+       "  /* draw centered vertical line to link estimators */\n",
+       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+       "  background-size: 2px 100%;\n",
+       "  background-repeat: no-repeat;\n",
+       "  background-position: center center;\n",
+       "}\n",
+       "\n",
+       "/* Parallel-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item::after {\n",
+       "  content: \"\";\n",
+       "  width: 100%;\n",
+       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+       "  flex-grow: 1;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel {\n",
+       "  display: flex;\n",
+       "  align-items: stretch;\n",
+       "  justify-content: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
+       "  align-self: flex-end;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
+       "  width: 0;\n",
+       "}\n",
+       "\n",
+       "/* Serial-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-serial {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "  align-items: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  padding-right: 1em;\n",
+       "  padding-left: 1em;\n",
+       "}\n",
+       "\n",
+       "\n",
+       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+       "clickable and can be expanded/collapsed.\n",
+       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+       "*/\n",
+       "\n",
+       "/* Pipeline and ColumnTransformer style (default) */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable {\n",
+       "  /* Default theme specific background. It is overwritten whether we have a\n",
+       "  specific estimator or a Pipeline/ColumnTransformer */\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable label */\n",
+       "#sk-container-id-1 label.sk-toggleable__label {\n",
+       "  cursor: pointer;\n",
+       "  display: block;\n",
+       "  width: 100%;\n",
+       "  margin-bottom: 0;\n",
+       "  padding: 0.5em;\n",
+       "  box-sizing: border-box;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
+       "  /* Arrow on the left of the label */\n",
+       "  content: \"▸\";\n",
+       "  float: left;\n",
+       "  margin-right: 0.25em;\n",
+       "  color: var(--sklearn-color-icon);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable content - dropdown */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable__content {\n",
+       "  max-height: 0;\n",
+       "  max-width: 0;\n",
+       "  overflow: hidden;\n",
+       "  text-align: left;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
+       "  margin: 0.2em;\n",
+       "  border-radius: 0.25em;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "  /* Expand drop-down */\n",
+       "  max-height: 200px;\n",
+       "  max-width: 100%;\n",
+       "  overflow: auto;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "  content: \"▾\";\n",
+       "}\n",
+       "\n",
+       "/* Pipeline/ColumnTransformer-specific style */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific style */\n",
+       "\n",
+       "/* Colorize estimator box */\n",
+       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-1 div.sk-label label {\n",
+       "  /* The background is the default theme color */\n",
+       "  color: var(--sklearn-color-text-on-default-background);\n",
+       "}\n",
+       "\n",
+       "/* On hover, darken the color of the background */\n",
+       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Label box, darken color on hover, fitted */\n",
+       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator label */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label label {\n",
+       "  font-family: monospace;\n",
+       "  font-weight: bold;\n",
+       "  display: inline-block;\n",
+       "  line-height: 1.2em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\n",
+       "#sk-container-id-1 div.sk-estimator {\n",
+       "  font-family: monospace;\n",
+       "  border: 1px dotted var(--sklearn-color-border-box);\n",
+       "  border-radius: 0.25em;\n",
+       "  box-sizing: border-box;\n",
+       "  margin-bottom: 0.5em;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-estimator.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "/* on hover */\n",
+       "#sk-container-id-1 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+       "\n",
+       "/* Common style for \"i\" and \"?\" */\n",
+       "\n",
+       ".sk-estimator-doc-link,\n",
+       "a:link.sk-estimator-doc-link,\n",
+       "a:visited.sk-estimator-doc-link {\n",
+       "  float: right;\n",
+       "  font-size: smaller;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1em;\n",
+       "  height: 1em;\n",
+       "  width: 1em;\n",
+       "  text-decoration: none !important;\n",
+       "  margin-left: 1ex;\n",
+       "  /* unfitted */\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted,\n",
+       "a:link.sk-estimator-doc-link.fitted,\n",
+       "a:visited.sk-estimator-doc-link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "/* Span, style for the box shown on hovering the info icon */\n",
+       ".sk-estimator-doc-link span {\n",
+       "  display: none;\n",
+       "  z-index: 9999;\n",
+       "  position: relative;\n",
+       "  font-weight: normal;\n",
+       "  right: .2ex;\n",
+       "  padding: .5ex;\n",
+       "  margin: .5ex;\n",
+       "  width: min-content;\n",
+       "  min-width: 20ex;\n",
+       "  max-width: 50ex;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  box-shadow: 2pt 2pt 4pt #999;\n",
+       "  /* unfitted */\n",
+       "  background: var(--sklearn-color-unfitted-level-0);\n",
+       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted span {\n",
+       "  /* fitted */\n",
+       "  background: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link:hover span {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+       "\n",
+       "#sk-container-id-1 a.estimator_doc_link {\n",
+       "  float: right;\n",
+       "  font-size: 1rem;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1rem;\n",
+       "  height: 1rem;\n",
+       "  width: 1rem;\n",
+       "  text-decoration: none;\n",
+       "  /* unfitted */\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>SVC(C=1)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;SVC<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.svm.SVC.html\">?<span>Documentation for SVC</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>SVC(C=1)</pre></div> </div></div></div></div>"
+      ],
+      "text/plain": [
+       "SVC(C=1)"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tuned_svc.best_estimator_"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "89470c7d",
+   "metadata": {},
+   "source": [
+    "##### `OptCV` tuning via `HillClimbing`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "f606284b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "                                                                                                              \r"
+     ]
+    }
+   ],
+   "source": [
+    "# 1. defining the tuned estimator\n",
+    "from sklearn.svm import SVC\n",
+    "from hyperactive.integrations.sklearn import OptCV\n",
+    "from hyperactive.opt import HillClimbing\n",
+    "\n",
+    "# picking the optimizer is the only part that changes!\n",
+    "hill_climbing_config = {\n",
+    "    \"search_space\": {\n",
+    "    \"C\": np.array([0.01, 0.1, 1, 10]),\n",
+    "    \"gamma\": np.array([0.0001, 0.01, 0.1, 1, 10]),\n",
+    "    },\n",
+    "    \"n_iter\": 100,\n",
+    "}\n",
+    "hill_climbing = HillClimbing(**hill_climbing_config)\n",
+    "\n",
+    "tuned_svc = OptCV(SVC(), optimizer=hill_climbing)\n",
+    "\n",
+    "# 2. fitting the tuned estimator = tuning the hyperparameters\n",
+    "from sklearn.datasets import load_iris\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "\n",
+    "X, y = load_iris(return_X_y=True)\n",
+    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)\n",
+    "\n",
+    "tuned_svc.fit(X_train, y_train)\n",
+    "\n",
+    "# 3. making predictions with the tuned estimator\n",
+    "y_pred = tuned_svc.predict(X_test)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1e7164df",
+   "metadata": {},
+   "source": [
+    "best parameters and best estimator - works as before!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "14710f3d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'C': np.float64(10.0), 'gamma': np.float64(0.1)}"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tuned_svc.best_params_"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "0a55cdd6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-2 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --sklearn-color-text: black;\n",
+       "  --sklearn-color-line: gray;\n",
+       "  /* Definition of color scheme for unfitted estimators */\n",
+       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
+       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+       "  --sklearn-color-unfitted-level-3: chocolate;\n",
+       "  /* Definition of color scheme for fitted estimators */\n",
+       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
+       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
+       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
+       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
+       "\n",
+       "  /* Specific color for light theme */\n",
+       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-icon: #696969;\n",
+       "\n",
+       "  @media (prefers-color-scheme: dark) {\n",
+       "    /* Redefinition of color scheme for dark theme */\n",
+       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-icon: #878787;\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 input.sk-hidden--visually {\n",
+       "  border: 0;\n",
+       "  clip: rect(1px 1px 1px 1px);\n",
+       "  clip: rect(1px, 1px, 1px, 1px);\n",
+       "  height: 1px;\n",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-dashed-wrapped {\n",
+       "  border: 1px dashed var(--sklearn-color-line);\n",
+       "  margin: 0 0.4em 0.5em 0.4em;\n",
+       "  box-sizing: border-box;\n",
+       "  padding-bottom: 0.4em;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-container {\n",
+       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+       "     so we also need the `!important` here to be able to override the\n",
+       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+       "  display: inline-block !important;\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-text-repr-fallback {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-parallel-item,\n",
+       "div.sk-serial,\n",
+       "div.sk-item {\n",
+       "  /* draw centered vertical line to link estimators */\n",
+       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+       "  background-size: 2px 100%;\n",
+       "  background-repeat: no-repeat;\n",
+       "  background-position: center center;\n",
+       "}\n",
+       "\n",
+       "/* Parallel-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item::after {\n",
+       "  content: \"\";\n",
+       "  width: 100%;\n",
+       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+       "  flex-grow: 1;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel {\n",
+       "  display: flex;\n",
+       "  align-items: stretch;\n",
+       "  justify-content: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item:first-child::after {\n",
+       "  align-self: flex-end;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item:only-child::after {\n",
+       "  width: 0;\n",
+       "}\n",
+       "\n",
+       "/* Serial-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-serial {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "  align-items: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  padding-right: 1em;\n",
+       "  padding-left: 1em;\n",
+       "}\n",
+       "\n",
+       "\n",
+       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+       "clickable and can be expanded/collapsed.\n",
+       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+       "*/\n",
+       "\n",
+       "/* Pipeline and ColumnTransformer style (default) */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable {\n",
+       "  /* Default theme specific background. It is overwritten whether we have a\n",
+       "  specific estimator or a Pipeline/ColumnTransformer */\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable label */\n",
+       "#sk-container-id-2 label.sk-toggleable__label {\n",
+       "  cursor: pointer;\n",
+       "  display: block;\n",
+       "  width: 100%;\n",
+       "  margin-bottom: 0;\n",
+       "  padding: 0.5em;\n",
+       "  box-sizing: border-box;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 label.sk-toggleable__label-arrow:before {\n",
+       "  /* Arrow on the left of the label */\n",
+       "  content: \"▸\";\n",
+       "  float: left;\n",
+       "  margin-right: 0.25em;\n",
+       "  color: var(--sklearn-color-icon);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable content - dropdown */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content {\n",
+       "  max-height: 0;\n",
+       "  max-width: 0;\n",
+       "  overflow: hidden;\n",
+       "  text-align: left;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content pre {\n",
+       "  margin: 0.2em;\n",
+       "  border-radius: 0.25em;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content.fitted pre {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "  /* Expand drop-down */\n",
+       "  max-height: 200px;\n",
+       "  max-width: 100%;\n",
+       "  overflow: auto;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "  content: \"▾\";\n",
+       "}\n",
+       "\n",
+       "/* Pipeline/ColumnTransformer-specific style */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific style */\n",
+       "\n",
+       "/* Colorize estimator box */\n",
+       "#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-2 div.sk-label label {\n",
+       "  /* The background is the default theme color */\n",
+       "  color: var(--sklearn-color-text-on-default-background);\n",
+       "}\n",
+       "\n",
+       "/* On hover, darken the color of the background */\n",
+       "#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Label box, darken color on hover, fitted */\n",
+       "#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator label */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label label {\n",
+       "  font-family: monospace;\n",
+       "  font-weight: bold;\n",
+       "  display: inline-block;\n",
+       "  line-height: 1.2em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\n",
+       "#sk-container-id-2 div.sk-estimator {\n",
+       "  font-family: monospace;\n",
+       "  border: 1px dotted var(--sklearn-color-border-box);\n",
+       "  border-radius: 0.25em;\n",
+       "  box-sizing: border-box;\n",
+       "  margin-bottom: 0.5em;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-estimator.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "/* on hover */\n",
+       "#sk-container-id-2 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-estimator.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+       "\n",
+       "/* Common style for \"i\" and \"?\" */\n",
+       "\n",
+       ".sk-estimator-doc-link,\n",
+       "a:link.sk-estimator-doc-link,\n",
+       "a:visited.sk-estimator-doc-link {\n",
+       "  float: right;\n",
+       "  font-size: smaller;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1em;\n",
+       "  height: 1em;\n",
+       "  width: 1em;\n",
+       "  text-decoration: none !important;\n",
+       "  margin-left: 1ex;\n",
+       "  /* unfitted */\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted,\n",
+       "a:link.sk-estimator-doc-link.fitted,\n",
+       "a:visited.sk-estimator-doc-link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "/* Span, style for the box shown on hovering the info icon */\n",
+       ".sk-estimator-doc-link span {\n",
+       "  display: none;\n",
+       "  z-index: 9999;\n",
+       "  position: relative;\n",
+       "  font-weight: normal;\n",
+       "  right: .2ex;\n",
+       "  padding: .5ex;\n",
+       "  margin: .5ex;\n",
+       "  width: min-content;\n",
+       "  min-width: 20ex;\n",
+       "  max-width: 50ex;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  box-shadow: 2pt 2pt 4pt #999;\n",
+       "  /* unfitted */\n",
+       "  background: var(--sklearn-color-unfitted-level-0);\n",
+       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted span {\n",
+       "  /* fitted */\n",
+       "  background: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link:hover span {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+       "\n",
+       "#sk-container-id-2 a.estimator_doc_link {\n",
+       "  float: right;\n",
+       "  font-size: 1rem;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1rem;\n",
+       "  height: 1rem;\n",
+       "  width: 1rem;\n",
+       "  text-decoration: none;\n",
+       "  /* unfitted */\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 a.estimator_doc_link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "#sk-container-id-2 a.estimator_doc_link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 a.estimator_doc_link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>SVC(C=np.float64(10.0), gamma=np.float64(0.1))</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;SVC<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.svm.SVC.html\">?<span>Documentation for SVC</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>SVC(C=np.float64(10.0), gamma=np.float64(0.1))</pre></div> </div></div></div></div>"
+      ],
+      "text/plain": [
+       "SVC(C=np.float64(10.0), gamma=np.float64(0.1))"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tuned_svc.best_estimator_"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "sktime-skpro-skbase-313",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/extension_templates/experiments.py b/extension_templates/experiments.py
index e9ecda17..35c6bac8 100644
--- a/extension_templates/experiments.py
+++ b/extension_templates/experiments.py
@@ -143,11 +143,13 @@ def _paramnames(self):
 
         Returns
         -------
-        list of str
+        list of str, or None
             The parameter names of the search parameters.
+            If not known or arbitrary, return None.
         """
         # for every instance, this should return the correct parameter names
         # i.e., the maximal set of keys of the dict expected by _score
+        # (if not known or arbitrary, return None)
         return ["score_param1", "score_param2"]
 
     # todo: implement this, mandatory
diff --git a/src/hyperactive/base/_experiment.py b/src/hyperactive/base/_experiment.py
index db5d2aeb..42d11d2b 100644
--- a/src/hyperactive/base/_experiment.py
+++ b/src/hyperactive/base/_experiment.py
@@ -35,8 +35,12 @@ def paramnames(self):
 
         Returns
         -------
-        list of str
+        list of str, or None
             The parameter names of the search parameters.
+
+            * If list of str, params in ``evaluate`` and ``score`` must match this list,
+              or a subset thereof.
+            * If None, arbitrary parameters can be passed to ``evaluate`` and ``score``.
         """
         return self._paramnames()
 
@@ -45,10 +49,11 @@ def _paramnames(self):
 
         Returns
         -------
-        list of str
+        list of str, or None
             The parameter names of the search parameters.
+            If not known or arbitrary, return None.
         """
-        raise NotImplementedError
+        return None
 
     def evaluate(self, params):
         """Evaluate the parameters.
@@ -66,8 +71,11 @@ def evaluate(self, params):
             Additional metadata about the search.
         """
         paramnames = self.paramnames()
-        if not set(params.keys()) <= set(paramnames):
-            raise ValueError("Parameters do not match.")
+        if paramnames is not None and not set(params.keys()) <= set(paramnames):
+            raise ValueError(
+                f"Parameters passed to {type(self)}.evaluate do not match: "
+                f"expected {paramnames}, got {list(params.keys())}."
+            )
         res, metadata = self._evaluate(params)
         res = np.float64(res)
         return res, metadata
diff --git a/src/hyperactive/base/_optimizer.py b/src/hyperactive/base/_optimizer.py
index 7ab8c68a..91210fc4 100644
--- a/src/hyperactive/base/_optimizer.py
+++ b/src/hyperactive/base/_optimizer.py
@@ -49,7 +49,13 @@ def get_experiment(self):
         BaseExperiment
             The experiment to optimize parameters for.
         """
-        return self._experiment
+        exp = self._experiment
+        exp_is_baseobj = isinstance(exp, BaseObject)
+        if not exp_is_baseobj or exp.get_tag("object_type") != "experiment":
+            from hyperactive.experiment.func import FunctionExperiment
+
+            exp = FunctionExperiment(exp)  # callable adapted to BaseExperiment
+        return exp
 
     def solve(self):
         """Run the optimization search process to maximize the experiment's score.
diff --git a/src/hyperactive/base/tests/test_dynamic_exp.py b/src/hyperactive/base/tests/test_dynamic_exp.py
new file mode 100644
index 00000000..a1a0af1f
--- /dev/null
+++ b/src/hyperactive/base/tests/test_dynamic_exp.py
@@ -0,0 +1,32 @@
+"""Test that old function signature can be passed as experiment."""
+# copyright: hyperactive developers, MIT License (see LICENSE file)
+
+
+def test_dynamic_exp():
+    """Test that old function signature can be passed as experiment."""
+
+    # 1. define the experiment
+    def parabola(opt):
+        return opt["x"] ** 2 + opt["y"] ** 2
+
+    # 2. set up the HillClimbing optimizer
+    import numpy as np
+
+    from hyperactive.opt import HillClimbing
+
+    hillclimbing_config = {
+        "search_space": {
+            "x": np.array([0, 1, 2]),
+            "y": np.array([0, 1, 2]),
+        },
+    }
+    hill_climbing = HillClimbing(**hillclimbing_config, experiment=parabola)
+
+    # 3. run the HillClimbing optimizer
+    hill_climbing.solve()
+
+    best_params = hill_climbing.best_params_
+    assert best_params is not None, "Best parameters should not be None"
+    assert isinstance(best_params, dict), "Best parameters should be a dictionary"
+    assert "x" in best_params, "Best parameters should contain 'x'"
+    assert "y" in best_params, "Best parameters should contain 'y'"
diff --git a/src/hyperactive/experiment/func.py b/src/hyperactive/experiment/func.py
new file mode 100644
index 00000000..e744544f
--- /dev/null
+++ b/src/hyperactive/experiment/func.py
@@ -0,0 +1,160 @@
+"""Dynamic experiment to allow passing of functions."""
+# copyright: hyperactive developers, MIT License (see LICENSE file)
+
+from hyperactive.base import BaseExperiment
+
+
+class FunctionExperiment(BaseExperiment):
+    """Experiment that wraps a function.
+
+    Takes a callable that evaluates parameters; exposes it as the ``evaluate`` method.
+
+    Assumes higher scores are better.
+
+    Parameters
+    ----------
+    func : callable
+        Function to evaluate parameters.
+
+        * if ``parametrization="dict"``, should accept a single argument
+          which is a dictionary with string keys, and return a float.
+        * if ``parametrization="kwargs"``, should accept keyword arguments
+          with string keys, and return a float.
+
+    parametrization : str, one of {"dict", "kwargs"}, default="dict"
+        The way parameters are passed to the function.
+
+    Example
+    -------
+    >>> from hyperactive.experiment.func import FunctionExperiment
+
+    Parameterized by a dictionary:
+    >>> def parabola(opt):
+    ...     return opt["x"]**2 + opt["y"]**2
+    >>> para_exp = FunctionExperiment(parabola)
+    >>> params = {"x": 1, "y": 2}
+    >>> score, add_info = para_exp.score(params)
+
+    Parameterized by keyword arguments:
+    >>> def parabola_kwargs(x, y):
+    ...     return x**2 + y**2
+    >>> para_exp_kwargs = FunctionExperiment(parabola_kwargs, parametrization="kwargs")
+    >>> score, add_info = para_exp_kwargs.score({"x": 1, "y": 2})
+    """  # noqa: E501
+
+    def __init__(self, func, parametrization="dict"):
+        self.func = func
+        self.parametrization = parametrization
+        super().__init__()
+
+    def _paramnames(self):
+        """Return the parameter names of the search.
+
+        Returns
+        -------
+        list of str
+            The parameter names of the search parameters.
+        """
+        if self.parametrization == "dict":
+            return None
+        elif self.parametrization == "kwargs":
+            import inspect
+
+            sig = inspect.signature(self.func)
+            return list(sig.parameters.keys())
+
+    def _evaluate(self, params):
+        """Evaluate the parameters.
+
+        Parameters
+        ----------
+        params : dict with string keys
+            Parameters to evaluate.
+
+        Returns
+        -------
+        float
+            The value of the parameters as per evaluation.
+        dict
+            Additional metadata about the search.
+        """
+        if self.parametrization == "dict":
+            loss = self.func(params)
+        elif self.parametrization == "kwargs":
+            loss = self.func(**params)
+        else:
+            raise ValueError(
+                f"Error in FunctionExperiment, "
+                f"unknown parametrization {self.parametrization}. "
+                "Use 'dict' or 'kwargs'."
+            )
+        return loss, {}
+
+    @classmethod
+    def get_test_params(cls, parameter_set="default"):
+        """Return testing parameter settings for the skbase object.
+
+        ``get_test_params`` is a unified interface point to store
+        parameter settings for testing purposes. This function is also
+        used in ``create_test_instance`` and ``create_test_instances_and_names``
+        to construct test instances.
+
+        ``get_test_params`` should return a single ``dict``, or a ``list`` of ``dict``.
+
+        Each ``dict`` is a parameter configuration for testing,
+        and can be used to construct an "interesting" test instance.
+        A call to ``cls(**params)`` should
+        be valid for all dictionaries ``params`` in the return of ``get_test_params``.
+
+        The ``get_test_params`` need not return fixed lists of dictionaries,
+        it can also return dynamic or stochastic parameter settings.
+
+        Parameters
+        ----------
+        parameter_set : str, default="default"
+            Name of the set of test parameters to return, for use in tests. If no
+            special parameters are defined for a value, will return `"default"` set.
+
+        Returns
+        -------
+        params : dict or list of dict, default = {}
+            Parameters to create testing instances of the class
+            Each dict are parameters to construct an "interesting" test instance, i.e.,
+            `MyClass(**params)` or `MyClass(**params[i])` creates a valid test instance.
+            `create_test_instance` uses the first (or only) dictionary in `params`
+        """
+
+        def _func1(x):
+            """Evaluate parameters. Used in tests."""
+            return x["x"] ** 2 + x["y"] ** 2
+
+        def _func2(x):
+            """Evaluate parameters. Used in tests."""
+            return x["x"] ** 2 - x["y"] ** 2 + 10 * x["x"] + 5 * x["z"]
+
+        def _func3(x, y, z):
+            """Evaluate parameters. Used in tests."""
+            return x**2 + y**2 - 3 * x + 2 * y + 1
+
+        params0 = {"func": _func1}
+        params1 = {"func": _func2}
+        params2 = {"func": _func3, "parametrization": "kwargs"}
+        return [params0, params1, params2]
+
+    @classmethod
+    def _get_score_params(self):
+        """Return settings for testing score/evaluate functions. Used in tests only.
+
+        Returns a list, the i-th element should be valid arguments for
+        self.evaluate and self.score, of an instance constructed with
+        self.get_test_params()[i].
+
+        Returns
+        -------
+        list of dict
+            The parameters to be used for scoring.
+        """
+        params0 = {"x": 0, "y": 0}
+        params1 = {"x": 1, "y": 1, "z": 2}
+        params2 = {"x": 3, "y": 4, "z": 5}
+        return [params0, params1, params2]
diff --git a/src/hyperactive/tests/test_all_objects.py b/src/hyperactive/tests/test_all_objects.py
index c78061c1..79cc256c 100644
--- a/src/hyperactive/tests/test_all_objects.py
+++ b/src/hyperactive/tests/test_all_objects.py
@@ -194,9 +194,10 @@ def test_paramnames(self, object_class):
         for inst, obj_param in zip(inst_params, obj_params):
             obj_inst = object_class(**inst)
             paramnames = obj_inst.paramnames()
-            assert set(obj_param.keys()) <= set(
-                paramnames
-            ), f"Parameter names do not match: {paramnames} != {obj_param}"
+            if paramnames is not None:
+                assert set(obj_param.keys()) <= set(
+                    paramnames
+                ), f"Parameter names do not match: {paramnames} != {obj_param}"
 
     def test_score_function(self, object_class):
         """Test that substituting into score works as intended."""