public static class SVM.NPL extends SVM
| Modifier and Type | Field and Description |
|---|---|
static double[] |
DEFAULT_CONSTRAINT_FACTORS |
ENABLE_LOAD_WITHOUT_LIBRARY, MAX_CPU| Constructor and Description |
|---|
NPL(double[][] data,
double[] labels,
double nplClass) |
NPL(double[][] data,
double[] labels,
double nplClass,
double constraint) |
NPL(double[][] data,
double[] labels,
double nplClass,
double constraint,
double[] constraintFactors,
Config config) |
NPL(LiquidData.Data data,
double nplClass) |
NPL(LiquidData.Data data,
double nplClass,
double constraint) |
NPL(LiquidData.Data data,
double nplClass,
double constraint,
double[] constraintFactors,
Config config) |
NPL(LiquidData data,
double nplClass) |
NPL(LiquidData data,
double nplClass,
double constraint) |
NPL(LiquidData data,
double nplClass,
double constraint,
double[] constraintFactors,
Config config) |
| Modifier and Type | Method and Description |
|---|---|
double[][] |
select(String... argv)
Selects the best hyperparameter pair according to validation error.
|
calculateDataCover, clean, finalize, getConfig, getCover, getLastResult, getSelectErrs, getSolutionCoeffs, getSolutionSVs, getTrainErrs, isSelected, isTrained, predict, readSVM, setConfig, setConfig, setConfig, setConfig, setConfigAll, test, test, trainpublic NPL(LiquidData data, double nplClass)
public NPL(LiquidData data, double nplClass, double constraint)
public NPL(LiquidData data, double nplClass, double constraint, double[] constraintFactors, Config config)
public NPL(LiquidData.Data data, double nplClass)
public NPL(LiquidData.Data data, double nplClass, double constraint)
public NPL(LiquidData.Data data, double nplClass, double constraint, double[] constraintFactors, Config config)
public NPL(double[][] data,
double[] labels,
double nplClass)
public NPL(double[][] data,
double[] labels,
double nplClass,
double constraint)
public NPL(double[][] data,
double[] labels,
double nplClass,
double constraint,
double[] constraintFactors,
Config config)
public double[][] select(String... argv)
SVMargv can be used by experts in the same way
as in the svm-select command line program of liquidSVM interface.
Most users should rather use Config.select in class SVMargv - further command line arguments (for experts)SVM.getSelectErrs()Copyright © 2018. All rights reserved.