SKPreprocessor(preprocessor::String,args::Dict=Dict())

A wrapper for Scikitlearn preprocessor functions. Invoking skpreprocessors() will list the acceptable and supported functions. Please check Scikitlearn documentation for arguments to pass.

Implements fit! and transform!.

SKLearner(learner::String, args::Dict=Dict())

A Scikitlearn wrapper to load the different machine learning models. Invoking sklearners() will list the available learners. Please consult Scikitlearn documentation for arguments to pass.

Implements fit! and transform!.

function sklearners()

List the available scikitlearn machine learners.

crossvalidate(pl::Machine,X::DataFrame,Y::Vector,sfunc::String="balanced_accuracy_score",nfolds=10)

Runs K-fold cross-validation using balanced accuracy as the default. It support the following metrics for classification:

• "accuracy_score"
• "balancedaccuracyscore"
• "cohenkappascore"
• "jaccard_score"
• "matthews_corrcoef"
• "hamming_loss"
• "zerooneloss"
• "f1_score"
• "precision_score"
• "recall_score"

and the following metrics for regression:

• "meansquarederror"
• "meansquaredlog_error"
• "medianabsoluteerror"
• "r2_score"
• "max_error"
• "explainedvariancescore"