smile.validation

Class ClassificationValidation<M>

java.lang.Object

smile.validation.ClassificationValidation<M>

Type Parameters:

M - the model type.

All Implemented Interfaces:

java.io.Serializable

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

Classification model validation results.

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
ConfusionMatrix	confusion The confusion matrix.
ClassificationMetrics	metrics The classification metrics.
M	model The model.
double[][]	posteriori The posteriori probability of prediction if the model is a soft classifier.
int[]	prediction The model prediction.
int[]	truth The true class labels of validation data.

Constructor Summary

Constructors

Constructor and Description
ClassificationValidation(M model, int[] truth, int[] prediction, double[][] posteriori, double fitTime, double scoreTime) Constructor of soft classifier validation.
ClassificationValidation(M model, int[] truth, int[] prediction, double fitTime, double scoreTime) Constructor.

Method Summary

Modifier and Type	Method and Description
static <M extends DataFrameClassifier> ClassificationValidations<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 Classifier<T>> ClassificationValidations<M>	of(Bag[] bags, T[] x, int[] y, java.util.function.BiFunction<T[],int[],M> trainer) Trains and validates a model on multiple train/validation split.
static <M extends DataFrameClassifier> ClassificationValidation<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 Classifier<T>> ClassificationValidation<M>	of(T[] x, int[] y, T[] testx, int[] testy, java.util.function.BiFunction<T[],int[],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 int[] truth

The true class labels of validation data.

prediction

public final int[] prediction

The model prediction.

posteriori

public final double[][] posteriori

The posteriori probability of prediction if the model is a soft classifier.

confusion

public final ConfusionMatrix confusion

The confusion matrix.

metrics

public final ClassificationMetrics metrics

The classification metrics.

Constructor Detail

ClassificationValidation

public ClassificationValidation(M model,
                                int[] truth,
                                int[] prediction,
                                double fitTime,
                                double scoreTime)

Constructor.

ClassificationValidation

public ClassificationValidation(M model,
                                int[] truth,
                                int[] prediction,
                                double[][] posteriori,
                                double fitTime,
                                double scoreTime)

Constructor of soft classifier validation.

Method Detail

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object

of

public static <T,M extends Classifier<T>> ClassificationValidation<M> of(T[] x,
                                                                         int[] y,
                                                                         T[] testx,
                                                                         int[] testy,
                                                                         java.util.function.BiFunction<T[],int[],M> trainer)

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

of

public static <T,M extends Classifier<T>> ClassificationValidations<M> of(Bag[] bags,
                                                                          T[] x,
                                                                          int[] y,
                                                                          java.util.function.BiFunction<T[],int[],M> trainer)

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

of

public static <M extends DataFrameClassifier> ClassificationValidation<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 DataFrameClassifier> ClassificationValidations<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.