Bootstrap
Bootstrap validation runner.
Functions
Link copied to clipboard
fun <T, M : Classifier<T>> classification(k: Int, x: Array<T>, y: IntArray, trainer: (Array<T>, IntArray) -> M): ClassificationValidations<M>
Bootstrap validation on a generic classifier. The bootstrap is a general tool for assessing statistical accuracy. The basic idea is to randomly draw datasets with replacement from the training data, each sample the same size as the original training set.
fun <M : DataFrameClassifier> classification(k: Int, formula: Formula, data: DataFrame, trainer: (Formula, DataFrame) -> M): ClassificationValidations<M>
Bootstrap validation on a data frame classifier.
Link copied to clipboard
fun <T, M : Regression<T>> regression(k: Int, x: Array<T>, y: DoubleArray, trainer: (Array<T>, DoubleArray) -> M): RegressionValidations<M>
Bootstrap validation on a generic regression model.
fun <M : DataFrameRegression> regression(k: Int, formula: Formula, data: DataFrame, trainer: (Formula, DataFrame) -> M): RegressionValidations<M>
Bootstrap validation on a data frame regression model.