model_evaluation

Module containing the model evaluation checks in the vision package.

Classes

TrainTestPredictionDrift	Calculate prediction drift between train dataset and test dataset, using statistical measures.
ClassPerformance	Summarize given metrics on a dataset and model.
ConfusionMatrixReport	Calculate the confusion matrix of the model on the given dataset.
ImageSegmentPerformance	Segment the data by various properties of the image, and compare the performance of the segments.
MeanAveragePrecisionReport	Summarize mean average precision metrics on a dataset and model per IoU and bounding box area.
MeanAverageRecallReport	Summarize mean average recall metrics on a dataset and model per detections and area range.
ModelErrorAnalysis	Find the properties that best split the data into segments of high and low model error.
RobustnessReport	Compare performance of model on original dataset and augmented dataset.
SimpleModelComparison	Compare given model score to simple model score (according to given model type).
SingleDatasetPerformance	Calculate performance metrics of a given model on a given dataset.
WeakSegmentsPerformance	Search for segments with low performance scores.

previous

TrainTestLabelDrift.update

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TrainTestPredictionDrift