[7.x][ML] Gain upper bound estimation for classification and regression #1568
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valeriy42 merged 4 commits intoelastic:7.xfrom Nov 12, 2020
Merged
[7.x][ML] Gain upper bound estimation for classification and regression #1568valeriy42 merged 4 commits intoelastic:7.xfrom
valeriy42 merged 4 commits intoelastic:7.xfrom
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…lastic#1537) In this PR we start computing an upper bound on the potential gain from splitting a node. If the upper bound of the gain is lower than the currently smallest gain among all candidates, we ignore the node and this way prevent computations that are especially expensive on the large datasets. Since we avoid computation of the splits that we wouldn't be added to the tree anyway, this PR does not change the qualitative results. At the moment, we can only compute the upper bound for regression and binary classification. For multiclass classification we proceed as before. Note: this PR contains additional instrumentation to assess the performance improvement. I will remove this instrumentation in a follow-up PR after tests.
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In this PR we start computing an upper bound on the potential gain from splitting a node. If the upper bound of the gain is lower than the currently smallest gain among all candidates, we ignore the node and this way prevent computations that are especially expensive on the large datasets.
Since we avoid computation of the splits that we wouldn't be added to the tree anyway, this PR does not change the qualitative results.
At the moment, we can only compute the upper bound for regression and binary classification. For multiclass classification we proceed as before.
Note: this PR contains additional instrumentation to assess the performance improvement. I will remove this instrumentation in a follow-up PR after tests.
Backport of #1537