smile.validation

Class RegressionValidation<M>

java.lang.Object

smile.validation.RegressionValidation<M>

Type Parameters:

M - the regression model type.

All Implemented Interfaces:

java.io.Serializable

public class RegressionValidation<M>
extends java.lang.Object
implements java.io.Serializable

Regression model validation results.

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
RegressionMetrics	metrics The regression metrics.
M	model The model.
double[]	prediction The model prediction.
double[]	truth The true response variable of validation data.

Constructor Summary

Constructors

Constructor and Description
RegressionValidation(M model, double[] truth, double[] prediction, RegressionMetrics metrics) Constructor.

Method Summary

Modifier and Type	Method and Description
static <M extends DataFrameRegression> RegressionValidations<M>	of(Bag[] bags, smile.data.formula.Formula formula, smile.data.DataFrame data, java.util.function.BiFunction<smile.data.formula.Formula,smile.data.DataFrame,M> trainer) Trains and validates a model on multiple train/validation split.
static <T,M extends Regression<T>> RegressionValidations<M>	of(Bag[] bags, T[] x, double[] y, java.util.function.BiFunction<T[],double[],M> trainer) Trains and validates a model on multiple train/validation split.
static <M extends DataFrameRegression> RegressionValidation<M>	of(smile.data.formula.Formula formula, smile.data.DataFrame train, smile.data.DataFrame test, java.util.function.BiFunction<smile.data.formula.Formula,smile.data.DataFrame,M> trainer) Trains and validates a model on a train/validation split.
static <T,M extends Regression<T>> RegressionValidation<M>	of(T[] x, double[] y, T[] testx, double[] testy, java.util.function.BiFunction<T[],double[],M> trainer) Trains and validates a model on a train/validation split.
java.lang.String	toString()

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

model

public final M model

The model.

truth

public final double[] truth

The true response variable of validation data.

prediction

public final double[] prediction

The model prediction.

metrics

public final RegressionMetrics metrics

The regression metrics.

Constructor Detail

RegressionValidation

public RegressionValidation(M model,
                            double[] truth,
                            double[] prediction,
                            RegressionMetrics metrics)

Constructor.

Method Detail

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object

of

public static <T,M extends Regression<T>> RegressionValidation<M> of(T[] x,
                                                                     double[] y,
                                                                     T[] testx,
                                                                     double[] testy,
                                                                     java.util.function.BiFunction<T[],double[],M> trainer)

Trains and validates a model on a train/validation split.

of

public static <T,M extends Regression<T>> RegressionValidations<M> of(Bag[] bags,
                                                                      T[] x,
                                                                      double[] y,
                                                                      java.util.function.BiFunction<T[],double[],M> trainer)

Trains and validates a model on multiple train/validation split.

of

public static <M extends DataFrameRegression> RegressionValidation<M> of(smile.data.formula.Formula formula,
                                                                         smile.data.DataFrame train,
                                                                         smile.data.DataFrame test,
                                                                         java.util.function.BiFunction<smile.data.formula.Formula,smile.data.DataFrame,M> trainer)

Trains and validates a model on a train/validation split.

of

public static <M extends DataFrameRegression> RegressionValidations<M> of(Bag[] bags,
                                                                          smile.data.formula.Formula formula,
                                                                          smile.data.DataFrame data,
                                                                          java.util.function.BiFunction<smile.data.formula.Formula,smile.data.DataFrame,M> trainer)

Trains and validates a model on multiple train/validation split.