Why?

[CeciAc]

@frgt10cs commented on Sat Jan 19 2019

Я делал всё по документации, код полностью идентичен (даже копировал-вставлял), в итоге результаты не сходятся. Ваши выходные данные:
Sentiment: This is a very rude movie | Prediction: Toxic | Probability: 0.4585565
Sentiment: He is the best, and the article should say that. | Prediction: Not Toxic | Probability: 0.9924279
Мои:
Sentiment: This is a very rude movie | Prediction: Toxic | Probability: 0,5297049
Sentiment: He is the best, and the article should say that. | Prediction: Toxic | Probability: 0,9918675
Что не так? Почему различие?

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Сведения о документе

⚠ Не вносите правки в этот раздел. Это необходимо для связывания страницы сайта docs.microsoft.com с вопросом на GitHub.

• ID: c8e22825-c4ee-5a36-f911-8ad456970ecc
• Version Independent ID: ad0bf640-7dfc-1184-077c-358bb14277a7
• Content: Использование ML.NET для анализа тональности методом двоичной классификации
• Content Source: docs/machine-learning/tutorials/sentiment-analysis.md
• Product: dotnet-ml
• GitHub Login: @JRAlexander
• Microsoft Alias: johalex

[CeciAc]

Hi team,
I'm moving this here since the user is having issues with the provided example
Rough translation:

I did everything according to the documentation, the code is completely identical (even copied-pasted), as a result, the results do not converge. Your output:
Sentiment: This is a very rude movie | Prediction: Toxic | Probability: 0.4585565
Sentiment: He is the best. | Prediction: Not Toxic | Probability: 0.9924279
My:
Sentiment: This is a very rude movie | Prediction: Toxic | Probability: 0.5297049
Sentiment: He is the best. | Prediction: Toxic | Probability: 0.9918675
What's wrong? Why the difference?

[rpetrusha]

@JRAlexander, can you take a look?

[JRAlexander]

Closing. Fixed with 11114