performance#
Module contains checks of model performance metrics.
Classes
Summarize given scores on a dataset and model. |
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Calculate the confusion matrix of the model on the given dataset. |
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Calculate the ROC curve for each class. |
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Compare given model score to simple model score (according to given model type). |
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Calculate the calibration curve with brier score for each class. |
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Display performance score segmented by 2 top (or given) features in a heatmap. |
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Check the regression systematic error. |
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Check regression error distribution. |
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Summarize performance scores for multiple models on test datasets. |
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Find features that best split the data into segments of high and low model error. |