Built-in Evaluators

The builtin module provides ready-to-use evaluator implementations for common machine learning tasks. These evaluators extend the base evaluator classes and provide specific functionality for classification, regression, dataset analysis, and model comparison.

Module Contents

Object	Description
BarPlot	Creates bar plots for categorical features.
CategoricalStatistics	Computes statistics for categorical variables in datasets.
CompareModels	Compares performance across multiple models.
ConfusionMatrix	Computes confusion matrix for classification models.
ContinuousStatistics	Computes statistics for continuous variables in datasets.
CorrelationMatrix	Creates correlation matrix plots.
EvaluateModel	Evaluates model performance using specified metrics.
EvaluateModelCV	Evaluates model performance using cross-validation.
Histogram	Creates histogram plots for dataset features.
HyperparameterTuning	Performs hyperparameter optimization.
PlotConfusionHeatmap	Creates confusion matrix heatmap plots.
PlotFeatureImportance	Creates feature importance plots.
PlotLearningCurve	Creates learning curve plots.
PlotModelComparison	Creates model comparison plots.
PlotPrecisionRecallCurve	Creates precision-recall curve plots.
PlotPredVsObs	Creates predicted vs observed plots for regression models.
PlotResiduals	Creates residual plots for regression models.
PlotRocCurve	Creates ROC curve plots for classification models.
PlotShapleyValues	Creates SHAP value plots for model interpretability.