smile-kotlin/smile.validation/CrossValidationRunner/regression

regression

fun <T, M : Regression<T>> regression(k: Int, x: Array<T>, y: DoubleArray, trainer: (Array<T>, DoubleArray) -> M): RegressionValidations<M>(source)

Cross validation on a generic regression model.

Return

validation results.

Parameters

k-fold cross validation.

data samples.

response variable.

trainer

a lambda to return a regression model trained on the given data.

fun <T, M : Regression<T>> regression(round: Int, k: Int, x: Array<T>, y: DoubleArray, trainer: (Array<T>, DoubleArray) -> M): RegressionValidations<M>(source)

Repeated cross validation on a generic regression model.

Return

validation results.

Parameters

round

the number of rounds of repeated cross validation.

k-fold cross validation.

data samples.

response variable.

trainer

a lambda to return a regression model trained on the given data.

fun <M : DataFrameRegression> regression(k: Int, formula: Formula, data: DataFrame, trainer: (Formula, DataFrame) -> M): RegressionValidations<M>(source)

Cross validation on a data frame regression model.

Return

validation results.

Parameters

k-fold cross validation.

formula

model formula.

data

data samples.

trainer

a lambda to return a regression model trained on the given data.

fun <M : DataFrameRegression> regression(round: Int, k: Int, formula: Formula, data: DataFrame, trainer: (Formula, DataFrame) -> M): RegressionValidations<M>(source)

Repeated cross validation on a data frame regression model.

Return

validation results.

Parameters

round

the number of rounds of repeated cross validation.

k-fold cross validation.

formula

model formula.

data

data samples.

trainer

a lambda to return a regression model trained on the given data.