public static class ModelMetricsSupervised.MetricBuilderSupervised<T extends ModelMetricsSupervised.MetricBuilderSupervised<T>> extends ModelMetrics.MetricBuilder<T>
Modifier and Type | Field and Description |
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protected java.lang.String[] |
_domain |
protected int |
_nclasses |
Constructor and Description |
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ModelMetricsSupervised.MetricBuilderSupervised(int nclasses,
java.lang.String[] domain) |
Modifier and Type | Method and Description |
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ModelMetrics |
makeModelMetrics(Model m,
Frame f,
Frame adaptedFrame,
Frame preds)
Create a model metrics object
|
double[] |
perRow(double[] ds,
float[] yact,
Model m) |
perRow, postGlobal, reduce, weightedSigma
asBytes, clone, copyOver, frozenType, read, readExternal, readJSON, reloadFromBytes, toJsonString, write, writeExternal, writeJSON
protected final java.lang.String[] _domain
protected final int _nclasses
public ModelMetricsSupervised.MetricBuilderSupervised(int nclasses, java.lang.String[] domain)
public double[] perRow(double[] ds, float[] yact, Model m)
perRow
in class ModelMetrics.MetricBuilder<T extends ModelMetricsSupervised.MetricBuilderSupervised<T>>
public ModelMetrics makeModelMetrics(Model m, Frame f, Frame adaptedFrame, Frame preds)
makeModelMetrics
in class ModelMetrics.MetricBuilder<T extends ModelMetricsSupervised.MetricBuilderSupervised<T>>
m
- Modelf
- FrameadaptedFrame
- preds
- Optional predictions (can be null), only used to compute Gains/Lift table for binomial problems @return