hex

Class ModelMetricsRegression.MetricBuilderRegression<T extends ModelMetricsRegression.MetricBuilderRegression<T>>

java.lang.Object

water.Iced

hex.ModelMetrics.MetricBuilder<T>

hex.ModelMetricsSupervised.MetricBuilderSupervised<T>

hex.ModelMetricsRegression.MetricBuilderRegression<T>

All Implemented Interfaces:

java.io.Externalizable, java.io.Serializable, java.lang.Cloneable, Freezable

Enclosing class:

ModelMetricsRegression

public static class ModelMetricsRegression.MetricBuilderRegression<T extends ModelMetricsRegression.MetricBuilderRegression<T>>
extends ModelMetricsSupervised.MetricBuilderSupervised<T>

See Also:

Serialized Form

Field Summary

Fields inherited from class hex.ModelMetricsSupervised.MetricBuilderSupervised

_domain, _nclasses

Fields inherited from class hex.ModelMetrics.MetricBuilder

_count, _sumsqe, _wcount, _work, _wY, _wYY

Constructor Summary

Constructors

Constructor and Description
ModelMetricsRegression.MetricBuilderRegression()
ModelMetricsRegression.MetricBuilderRegression(Distribution dist)

Method Summary

Methods

Modifier and Type	Method and Description
ModelMetrics	makeModelMetrics(Model m, Frame f, Frame adaptedFrame, Frame preds) Create a model metrics object
double[]	perRow(double[] ds, float[] yact, double w, double o, Model m)
double[]	perRow(double[] ds, float[] yact, Model m)
void	reduce(T mb)

Methods inherited from class hex.ModelMetrics.MetricBuilder

postGlobal, weightedSigma

Methods inherited from class water.Iced

asBytes, clone, copyOver, frozenType, read, readExternal, readJSON, reloadFromBytes, toJsonString, write, writeExternal, writeJSON

Methods inherited from class java.lang.Object

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

Constructor Detail

ModelMetricsRegression.MetricBuilderRegression

public ModelMetricsRegression.MetricBuilderRegression()

ModelMetricsRegression.MetricBuilderRegression

public ModelMetricsRegression.MetricBuilderRegression(Distribution dist)

Method Detail

perRow

public double[] perRow(double[] ds,
              float[] yact,
              Model m)

Overrides:

perRow in class ModelMetricsSupervised.MetricBuilderSupervised<T extends ModelMetricsRegression.MetricBuilderRegression<T>>

perRow

public double[] perRow(double[] ds,
              float[] yact,
              double w,
              double o,
              Model m)

Overrides:

perRow in class ModelMetrics.MetricBuilder<T extends ModelMetricsRegression.MetricBuilderRegression<T>>

reduce

public void reduce(T mb)

Overrides:

reduce in class ModelMetrics.MetricBuilder<T extends ModelMetricsRegression.MetricBuilderRegression<T>>

makeModelMetrics

public ModelMetrics makeModelMetrics(Model m,
                            Frame f,
                            Frame adaptedFrame,
                            Frame preds)

Description copied from class: ModelMetricsSupervised.MetricBuilderSupervised

Create a model metrics object

Overrides:

makeModelMetrics in class ModelMetricsSupervised.MetricBuilderSupervised<T extends ModelMetricsRegression.MetricBuilderRegression<T>>

Parameters:

m - Model

f - Frame

adaptedFrame - Adapted Frame

preds - Optional predictions (can be null), only used to compute Gains/Lift table for binomial problems @return