public class PCAMojoModel extends MojoModel
Modifier and Type | Field and Description |
---|---|
int[] |
_catOffsets |
int |
_eigenVectorSize |
int |
_k |
int |
_ncats |
int |
_nnums |
double[] |
_normMul |
double[] |
_normSub |
java.lang.String |
_pca_impl |
java.lang.String |
_pca_method |
int[] |
_permutation |
boolean |
_use_all_factor_levels |
_algoName, _balanceClasses, _category, _defaultThreshold, _h2oVersion, _modelAttributes, _modelClassDistrib, _modelDescriptor, _mojo_version, _nclasses, _nfeatures, _priorClassDistrib, _reproducibilityInformation, _supervised, _uuid
_domains, _foldColumn, _names, _offsetColumn, _responseColumn, _treatmentColumn
Constructor and Description |
---|
PCAMojoModel(java.lang.String[] columns,
java.lang.String[][] domains,
java.lang.String responseColumn) |
Modifier and Type | Method and Description |
---|---|
java.lang.String[] |
getOutputNames() |
int |
getPredsSize()
Returns the expected size of preds array which is passed to `predict(double[], double[])` function.
|
int |
nclasses()
Returns number of output classes for classifiers, 1 for regression models, and 0 for unsupervised models.
|
double[] |
score0(double[] row,
double[] preds)
Subclasses implement the scoring logic.
|
getModelCategory, getUUID, isSupervised, load, load, load, nfeatures
bitSetContains, bitSetIsInRange, calibrateClassProbabilities, convertDouble2Float, correctProbabilities, createAuxKey, features, GBM_rescale, getCategoricalEncoding, getColIdx, getDomainValues, getDomainValues, getDomainValues, getHeader, getModelCategories, getNames, getNumClasses, getNumCols, getNumResponseClasses, getOffsetName, getOrigDomainValues, getOrigNames, getOrigNumCols, getOrigProjectionArray, getOutputDomains, getPrediction, getPredictionBinomial, getPredictionMultinomial, getPredsSize, getResponseIdx, getResponseName, GLM_identityInv, GLM_inverseInv, GLM_logInv, GLM_logitInv, GLM_ologitInv, GLM_tweedieInv, img2pixels, internal_threadSafeInstance, isAutoEncoder, isClassifier, KMeans_closest, KMeans_distance, KMeans_distance, KMeans_distances, Kmeans_preprocessData, Kmeans_preprocessData, KMeans_simplex, log_rescale, mapEnum, nCatFeatures, requiresOffset, score0, setCats, setCats, setInput, setInput
public int[] _catOffsets
public int[] _permutation
public int _ncats
public int _nnums
public double[] _normSub
public double[] _normMul
public boolean _use_all_factor_levels
public java.lang.String _pca_method
public java.lang.String _pca_impl
public int _k
public int _eigenVectorSize
public PCAMojoModel(java.lang.String[] columns, java.lang.String[][] domains, java.lang.String responseColumn)
public double[] score0(double[] row, double[] preds)
GenModel
public int getPredsSize()
GenModel
getPredsSize
in interface IGeneratedModel
getPredsSize
in class GenModel
public int nclasses()
GenModel
public java.lang.String[] getOutputNames()
getOutputNames
in class GenModel