rdkit.ML.NaiveBayes.CrossValidate module

handles doing cross validation with naive bayes models and evaluation of individual models

rdkit.ML.NaiveBayes.CrossValidate.CrossValidate(NBmodel, testExamples, appendExamples=0)

rdkit.ML.NaiveBayes.CrossValidate.CrossValidationDriver(examples, attrs, nPossibleValues, nQuantBounds, mEstimateVal=0.0, holdOutFrac=0.3, modelBuilder=<function makeNBClassificationModel>, silent=0, calcTotalError=0, **kwargs)

rdkit.ML.NaiveBayes.CrossValidate.makeNBClassificationModel(trainExamples, attrs, nPossibleValues, nQuantBounds, mEstimateVal=-1.0, useSigs=False, ensemble=None, useCMIM=0, **kwargs)