public abstract class XGBoostMojoModel
extends hex.genmodel.MojoModel
implements hex.genmodel.algos.tree.SharedTreeGraphConverter, java.io.Closeable
| Modifier and Type | Class and Description |
|---|---|
static class |
XGBoostMojoModel.ObjectiveType |
| Modifier and Type | Field and Description |
|---|---|
int[] |
_catOffsets |
int |
_cats |
java.lang.String |
_featureMap |
int |
_nums |
boolean |
_sparse |
boolean |
_useAllFactorLevels |
| Constructor and Description |
|---|
XGBoostMojoModel(java.lang.String[] columns,
java.lang.String[][] domains,
java.lang.String responseColumn) |
| Modifier and Type | Method and Description |
|---|---|
protected hex.genmodel.algos.tree.SharedTreeGraph |
_computeGraph(biz.k11i.xgboost.gbm.GradBooster booster,
int treeNumber) |
protected void |
constructSubgraph(biz.k11i.xgboost.tree.RegTreeNode[] xgBoostNodes,
hex.genmodel.algos.tree.SharedTreeNode sharedTreeNode,
int nodeIndex,
hex.genmodel.algos.tree.SharedTreeSubgraph sharedTreeSubgraph,
boolean[] oneHotEncodedMap,
boolean inclusiveNA,
java.lang.String[] features) |
protected boolean[] |
markOneHotEncodedCategoricals(java.lang.String[] featureMap) |
void |
postReadInit() |
double[] |
score0(double[] row,
double[] preds) |
static double[] |
toPreds(double[] in,
float[] out,
double[] preds,
int nclasses,
double[] priorClassDistrib,
double defaultThreshold) |
getModelCategory, getUUID, isSupervised, load, load, nclasses, nfeaturesbitSetContains, bitSetIsInRange, calibrateClassProbabilities, convertDouble2Float, correctProbabilities, createAuxKey, GBM_rescale, getColIdx, getDomainValues, getDomainValues, getDomainValues, getHeader, getModelCategories, getNames, getNumClasses, getNumCols, getNumResponseClasses, getPrediction, getPredsSize, getPredsSize, getResponseIdx, getResponseName, GLM_identityInv, GLM_inverseInv, GLM_logInv, GLM_logitInv, GLM_ologitInv, GLM_tweedieInv, img2pixels, isAutoEncoder, isClassifier, KMeans_closest, KMeans_distance, KMeans_distance, KMeans_distances, Kmeans_preprocessData, Kmeans_preprocessData, KMeans_simplex, log_rescale, mapEnum, score0, setCats, setCats, setInput, setInputpublic int _nums
public int _cats
public int[] _catOffsets
public boolean _useAllFactorLevels
public boolean _sparse
public java.lang.String _featureMap
public XGBoostMojoModel(java.lang.String[] columns,
java.lang.String[][] domains,
java.lang.String responseColumn)
public void postReadInit()
public final double[] score0(double[] row,
double[] preds)
score0 in class hex.genmodel.GenModelpublic static double[] toPreds(double[] in,
float[] out,
double[] preds,
int nclasses,
double[] priorClassDistrib,
double defaultThreshold)
protected void constructSubgraph(biz.k11i.xgboost.tree.RegTreeNode[] xgBoostNodes,
hex.genmodel.algos.tree.SharedTreeNode sharedTreeNode,
int nodeIndex,
hex.genmodel.algos.tree.SharedTreeSubgraph sharedTreeSubgraph,
boolean[] oneHotEncodedMap,
boolean inclusiveNA,
java.lang.String[] features)
protected boolean[] markOneHotEncodedCategoricals(java.lang.String[] featureMap)
protected hex.genmodel.algos.tree.SharedTreeGraph _computeGraph(biz.k11i.xgboost.gbm.GradBooster booster,
int treeNumber)