Uses of Class
io.github.metarank.lightgbm4j.LGBMException

Packages that use LGBMException

Package	Description
io.github.metarank.lightgbm4j

Uses of LGBMException in io.github.metarank.lightgbm4j

Methods in io.github.metarank.lightgbm4j that throw LGBMException

Modifier and Type	Method	Description
void	LGBMBooster.addValidData(LGBMDataset dataset)	Add new validation data to booster.
void	LGBMBooster.close()	Deallocate all native memory for the LightGBM model.
void	LGBMDataset.close()	Deallocate all native memory for the LightGBM dataset.
static LGBMBooster	LGBMBooster.create(LGBMDataset dataset, String parameters)	Create a new boosting learner.
static LGBMDataset	LGBMDataset.createFromFile(String fileName, String parameters, LGBMDataset reference)	Load dataset from file (like LightGBM CLI version does).
static LGBMDataset	LGBMDataset.createFromMat(double[] data, int rows, int cols, boolean isRowMajor, String parameters, LGBMDataset reference)	Create dataset from dense double[] matrix.
static LGBMDataset	LGBMDataset.createFromMat(float[] data, int rows, int cols, boolean isRowMajor, String parameters, LGBMDataset reference)	Create dataset from dense float[] matrix.
static LGBMBooster	LGBMBooster.createFromModelfile(String file)	Load an existing booster from model file.
void	LGBMDataset.dumpText(String fileName)	Dumps dataset into a file for debugging.
double[]	LGBMBooster.featureImportance(int numIteration, LGBMBooster.FeatureImportanceType importanceType)	Get model feature importance.
double[]	LGBMBooster.getEval(int dataIndex)	Get evaluation for training data and validation data.
String[]	LGBMBooster.getEvalNames()	Get names of evaluation datasets.
String[]	LGBMBooster.getFeatureNames()	Get names of features.
String[]	LGBMDataset.getFeatureNames()	Gets feature names from dataset, if dataset supports it.
float[]	LGBMDataset.getFieldFloat(String field)	Get float[] field from the dataset.
int[]	LGBMDataset.getFieldInt(String field)	Get int[] field from the dataset.
int	LGBMBooster.getNumClasses()	Get number of classes.
int	LGBMDataset.getNumData()	Get number of data points.
int	LGBMBooster.getNumFeature()	Get number of features.
int	LGBMDataset.getNumFeatures()	Get number of features.
long	LGBMBooster.getNumPredict(int dataIdx)	Get number of predictions for training data and validation data (this can be used to support customized evaluation functions).
double[]	LGBMBooster.getPredict(int dataIdx)	Get prediction for training data and validation data.
static LGBMBooster	LGBMBooster.loadModelFromString(String model)	Load an existing booster from string.
double[]	LGBMBooster.predictForMat(double[] input, int rows, int cols, boolean isRowMajor, PredictionType predictionType)
double[]	LGBMBooster.predictForMat(double[] input, int rows, int cols, boolean isRowMajor, PredictionType predictionType, String parameter)	Make prediction for a new double[] dataset.
double[]	LGBMBooster.predictForMat(float[] input, int rows, int cols, boolean isRowMajor, PredictionType predictionType)
double[]	LGBMBooster.predictForMat(float[] input, int rows, int cols, boolean isRowMajor, PredictionType predictionType, String parameter)	Make prediction for a new float[] dataset.
double	LGBMBooster.predictForMatSingleRow(double[] data, PredictionType predictionType)	Make prediction for a new double[] row dataset.
double	LGBMBooster.predictForMatSingleRow(float[] data, PredictionType predictionType)	Make prediction for a new float[] row dataset.
double	LGBMBooster.predictForMatSingleRowFast(LGBMBooster.FastConfig config, double[] data, PredictionType predictionType)
double	LGBMBooster.predictForMatSingleRowFast(LGBMBooster.FastConfig config, float[] data, PredictionType predictionType)
LGBMBooster.FastConfig	LGBMBooster.predictForMatSingleRowFastInit(PredictionType predictionType, int dtype, int ncols, String parameter)
String	LGBMBooster.saveModelToString(int startIteration, int numIteration, LGBMBooster.FeatureImportanceType featureImportance)	Save model to string.
void	LGBMDataset.setFeatureNames(String[] featureNames)	Set feature names
void	LGBMDataset.setField(String fieldName, double[] data)	Sets a double field.
void	LGBMDataset.setField(String fieldName, float[] data)	Sets a double field.
void	LGBMDataset.setField(String fieldName, int[] data)	Sets an int field.
boolean	LGBMBooster.updateOneIter()	Update the model for one iteration.
boolean	LGBMBooster.updateOneIterCustom(float[] grad, float[] hess)	Update the model by specifying gradient and Hessian directly (this can be used to support customized loss functions).