hex

Class ModelMetricsBinomialUplift

java.lang.Object

water.Iced<T>

water.Keyed<ModelMetrics>

hex.ModelMetrics

hex.ModelMetricsSupervised

hex.ModelMetricsBinomialUplift

All Implemented Interfaces:

java.io.Externalizable, java.io.Serializable, java.lang.Cloneable, Freezable<ModelMetrics>

public class ModelMetricsBinomialUplift
extends ModelMetricsSupervised

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	ModelMetricsBinomialUplift.MetricBuilderBinomialUplift

Nested classes/interfaces inherited from class hex.ModelMetricsSupervised

ModelMetricsSupervised.MetricBuilderSupervised<T extends ModelMetricsSupervised.MetricBuilderSupervised<T>>

Nested classes/interfaces inherited from class hex.ModelMetrics

ModelMetrics.MetricBuilder<T extends ModelMetrics.MetricBuilder<T>>

Field Summary

Fields

Modifier and Type	Field and Description
AUUC	_auuc

Fields inherited from class hex.ModelMetricsSupervised

_domain, _sigma

Fields inherited from class hex.ModelMetrics

_custom_metric, _description, _MSE, _nobs, _scoring_time

Fields inherited from class water.Keyed

_key

Constructor Summary

Constructors

Constructor and Description
ModelMetricsBinomialUplift(Model model, Frame frame, long nobs, java.lang.String[] domain, double sigma, AUUC auuc, CustomMetric customMetric)

Method Summary

Modifier and Type	Method and Description
protected java.lang.StringBuilder	appendToStringMetrics(java.lang.StringBuilder sb)
double	auuc()
double	auucNormalized()
static ModelMetricsBinomialUplift	getFromDKV(Model model, Frame frame)
static ModelMetricsBinomialUplift	make(Vec targetClassProbs, Vec actualLabels, Vec treatment, AUUC.AUUCType auucType, int nbins) Build a Binomial ModelMetrics object from target-class probabilities, from actual labels, and a given domain for both labels (and domain[1] is the target class)
static ModelMetricsBinomialUplift	make(Vec targetClassProbs, Vec actualLabels, Vec treatment, java.lang.String[] domain, AUUC.AUUCType auucType, int auucNbins) Build a Binomial ModelMetrics object from target-class probabilities, from actual labels, and a given domain for both labels (and domain[1] is the target class)
int	nbins()
double	qini()
java.lang.String	toString()

Methods inherited from class hex.ModelMetricsSupervised

r2

Methods inherited from class hex.ModelMetrics

auc_obj, buildKey, buildKey, calcVarImp, calcVarImp, calcVarImp, calcVarImp, checksum_impl, cm, deepCloneWithDifferentModelAndFrame, defaultModelMetrics, frame, getAllowedMetrics, getMetricFromModel, getMetricFromModelMetric, hr, isForFrame, isForModel, model, mse, residual_degrees_of_freedom, rmse, setModelKey, sortModelsByMetric, sortModelsByMetric, withDescription, withModelAndFrame

Methods inherited from class water.Keyed

checksum_impl, checksum, checksum, getKey, makeSchema, readAll_impl, readAll, remove_impl, remove_impl, remove_self_key_impl, remove, remove, remove, remove, remove, remove, removeQuietly, writeAll_impl, writeAll

Methods inherited from class water.Iced

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

Methods inherited from class java.lang.Object

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

Field Detail

_auuc

public final AUUC _auuc

Constructor Detail

ModelMetricsBinomialUplift

public ModelMetricsBinomialUplift(Model model,
                                  Frame frame,
                                  long nobs,
                                  java.lang.String[] domain,
                                  double sigma,
                                  AUUC auuc,
                                  CustomMetric customMetric)

Method Detail

getFromDKV

public static ModelMetricsBinomialUplift getFromDKV(Model model,
                                                    Frame frame)

toString

public java.lang.String toString()

Overrides:

toString in class ModelMetricsSupervised

auuc

public double auuc()

qini

public double qini()

auucNormalized

public double auucNormalized()

nbins

public int nbins()

appendToStringMetrics

protected java.lang.StringBuilder appendToStringMetrics(java.lang.StringBuilder sb)

Overrides:

appendToStringMetrics in class ModelMetrics

make

public static ModelMetricsBinomialUplift make(Vec targetClassProbs,
                                              Vec actualLabels,
                                              Vec treatment,
                                              AUUC.AUUCType auucType,
                                              int nbins)

Build a Binomial ModelMetrics object from target-class probabilities, from actual labels, and a given domain for both labels (and domain[1] is the target class)

Parameters:

targetClassProbs - A Vec containing target class probabilities

actualLabels - A Vec containing the actual labels (can be for fewer labels than what's in domain, since the predictions can be for a small subset of the data)

Returns:

ModelMetrics object

make

public static ModelMetricsBinomialUplift make(Vec targetClassProbs,
                                              Vec actualLabels,
                                              Vec treatment,
                                              java.lang.String[] domain,
                                              AUUC.AUUCType auucType,
                                              int auucNbins)

Build a Binomial ModelMetrics object from target-class probabilities, from actual labels, and a given domain for both labels (and domain[1] is the target class)

Parameters:

targetClassProbs - A Vec containing target class probabilities

actualLabels - A Vec containing the actual labels (can be for fewer labels than what's in domain, since the predictions can be for a small subset of the data)

treatment - A Vec containing the treatment values

domain - The two class labels (domain[0] is the non-target class, domain[1] is the target class, for which probabilities are given)

auucType - Type of default AUUC

auucNbins - Number of bins to calculate AUUC (-1 means default value 1000, the number has to be higher than zero)

Returns:

ModelMetrics object