hex.genmodel.easy.prediction

Class BinomialModelPrediction

java.lang.Object

hex.genmodel.easy.prediction.AbstractPrediction

hex.genmodel.easy.prediction.BinomialModelPrediction

All Implemented Interfaces:

java.io.Serializable

public class BinomialModelPrediction
extends AbstractPrediction

Binomial classification model prediction. GLM logistic regression (GLM family "binomial") also falls into this category.

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
double[]	calibratedClassProbabilities Class probabilities calibrated by Platt Scaling.
double[]	classProbabilities This array of length two has the class probability for each class (aka categorical or factor level) in the response column.
java.lang.String	label Label of the predicted level.
int	labelIndex 0 or 1.

Constructor Summary

Constructors

Constructor and Description
BinomialModelPrediction()

Method Summary

Methods inherited from class java.lang.Object

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

Field Detail

labelIndex

public int labelIndex

0 or 1.

label

public java.lang.String label

Label of the predicted level.

classProbabilities

public double[] classProbabilities

This array of length two has the class probability for each class (aka categorical or factor level) in the response column. The array corresponds to the level names returned by:

 model.getDomainValues(model.getResponseIdx())
 

"Domain" is the internal H2O term for level names. The values in this array may be Double.NaN, which means NA (this will happen with GLM, for example, if one of the input values for a new data point is NA). If they are valid numeric values, then they will sum up to 1.0.

calibratedClassProbabilities

public double[] calibratedClassProbabilities

Class probabilities calibrated by Platt Scaling. Optional, only calculated if the model supports it.

Constructor Detail

BinomialModelPrediction

public BinomialModelPrediction()