GLM (h2o-algos 3.46.0 API)

java.lang.Object
- water.Iced
- - hex.ModelBuilder<GLMModel,GLMModel.GLMParameters,GLMModel.GLMOutput>
  - - hex.glm.GLM

All Implemented Interfaces:

java.io.Externalizable, java.io.Serializable, java.lang.Cloneable, water.Freezable
```
public class GLM
extends hex.ModelBuilder<GLMModel,GLMModel.GLMParameters,GLMModel.GLMOutput>
```
Created by tomasnykodym on 8/27/14. Generalized linear model implementation.

See Also:

Serialized Form

Nested Class Summary

Nested Classes
Modifier and Type	Class and Description
`class`	`GLM.BetaConstraint`
`static class`	`GLM.BetaInfo`
`class`	`GLM.GLMDriver` Main loop of the glm algo.
`static class`	`GLM.GLMGradientInfo`
`static class`	`GLM.GLMGradientSolver` Gradient and line search computation for L_BFGS and also L_BFGS solver wrapper (for ADMM)
`static class`	`GLM.GramSolver` Created by tomasnykodym on 3/30/15.
`static class`	`GLM.PlugValuesImputer`
`static class`	`GLM.ProximalGradientInfo`
`static class`	`GLM.ProximalGradientSolver` Simple wrapper around ginfo computation, adding proximal penalty

Nested classes/interfaces inherited from class hex.ModelBuilder
hex.ModelBuilder.BuilderVisibility, hex.ModelBuilder.Driver, hex.ModelBuilder.FilterCols, hex.ModelBuilder.ModelTrainingCoordinator, hex.ModelBuilder.ValidationMessage

Field Summary

Fields
Modifier and Type	Field and Description
`GLM.BetaInfo`	`_betaInfo`
`int[][]`	`_gamColIndices`
`java.lang.String[][]`	`_gamColnames`
`java.lang.String`	`_generatedWeights`
`double[][][]`	`_penaltyMatrix`
`int[]`	`_randC`
`java.lang.String[]`	`_randCoeffNames`
`java.lang.String[]`	`_randomColNames`
`static int`	`SCORING_INTERVAL_MSEC`
`protected static long`	`WORK_TOTAL`

Fields inherited from class hex.ModelBuilder
_coordinator, _desc, _eventPublisher, _fold, _input_parms, _job, _messages, _nclass, _offset, _orig_projection_array, _origDomains, _origNames, _origTrain, _parms, _priorClassDist, _removedCols, _response, _result, _startUpOnceModelBuilder, _train, _treatment, _valid, _vresponse, _weights

Constructor Summary

Constructors
Constructor and Description
`GLM(boolean startup_once)`
`GLM(GLMModel.GLMParameters parms)`
`GLM(GLMModel.GLMParameters parms, double[][][] penaltyMatrix, java.lang.String[][] gamColnames)` This constructor is only called by GAM when it is trying to build a GAM model using GLM.
`GLM(GLMModel.GLMParameters parms, water.Key dest)`

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`hex.ModelCategory[]`	`can_build()`
`protected void`	`checkMemoryFootPrint(DataInfo activeData)`
`double[]`	`COD_solve(ComputationState.GramXY gram, double alpha, double lambda)`
`void`	`computeCrossValidation()` GLM implementation of N-fold cross-validation.
`protected boolean`	`computePriorClassDistribution()`
`void`	`copyUserInitialValues(int fixedEffectSize, int randomEffectSize, double[] beta, double[] ubeta, double[] phi, double hlcorrection, double[] psi, water.fvec.Frame randWeights, java.lang.String[] randCoeffNames)` This method performs a simple copying of user provided initial values to parameters - beta, ubeta, phi, tau, psi, init_sig_u
`void`	`cv_computeAndSetOptimalParameters(hex.ModelBuilder[] cvModelBuilders)` If run with lambda search, we need to take extra action performed after cross-val models are built.
`static int[]`	`findIterIndexAcrossFolds(java.util.List<java.lang.Integer>[] cvModelIters, int fold0Index)` This method is used to locate common iteration indices across all folds.
`boolean`	`haveMojo()`
`boolean`	`havePojo()`
`void`	`init(boolean expensive)`
`boolean`	`isSupervised()`
`int`	`nclasses()`
`double`	`restrictMag(double val)`
`void`	`setHGLMInitValues(double[] beta)` initialize the following parameters for HGLM from either user initial inputs or from a GLM model if user did not provide any starting values.
`protected static double`	`sparseOffset(double[] beta, DataInfo dinfo)`
`protected GLM.GLMDriver`	`trainModelImpl()`

Methods inherited from class hex.ModelBuilder
algoName, algos, builderVisibility, canLearnFromNAs, checkCustomMetricForEarlyStopping, checkDistributions, checkEarlyStoppingReproducibility, checkMemoryFootPrint_impl, checkMemoryFootPrint, checkResponseVariable, clearInitState, clearValidationErrors, cv_buildModels, cv_canBuildMainModelInParallel, cv_initStoppingParameters, cv_mainModelScores, cv_makeAggregateModelMetrics, cv_scoreCVModels, cv_updateOptimalParameters, defaultKey, desiredChunks, dest, error_count, error, get, getMessagesByFieldAndSeverity, getName, getSysProperty, getToEigenVec, hasFoldCol, hasOffsetCol, hasTreatmentCol, hasWeightCol, hide, ignoreBadColumns, ignoreConstColumns, ignoreInvalidColumns, ignoreStringColumns, ignoreUuidColumns, info, init_adaptFrameToTrain, init_getNClass, initWorkspace, isClassifier, isResponseOptional, isStopped, javaName, logMe, make, make, make, makeCVMetrics, makeCVModelBuilder, makeParameters, makePojoWriter, message, nFoldCV, nFoldWork, nModelsInParallel, nModelsInParallel, nModelsInParallel, numSpecialCols, paramName, raiseReproducibilityWarning, rebalance, remainingTimeSecs, response, schemaDirectory, separateFeatureVecs, setMaxRuntimeSecsForMainModel, setTrain, setValid, shouldReorder, smallDataSize, stop_requested, timeout, train, trainModel, trainModel, trainModelNested, trainModelNested, trainModelOnH2ONode, valid, validateBinaryResponse, validateStoppingMetric, validationErrors, validationWarnings, vresponse, warn

Methods inherited from class water.Iced
asBytes, clone, copyOver, frozenType, read, readExternal, readJSON, reloadFromBytes, toJsonBytes, toJsonString, write, writeExternal, writeJSON

Methods inherited from class java.lang.Object
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Field Detail
  - SCORING_INTERVAL_MSEC
```
public static final int SCORING_INTERVAL_MSEC
```
    See Also:
    
    Constant Field Values
  - _randC
```
public int[] _randC
```
  - _generatedWeights
```
public java.lang.String _generatedWeights
```
  - _randCoeffNames
```
public java.lang.String[] _randCoeffNames
```
  - _randomColNames
```
public java.lang.String[] _randomColNames
```
  - _penaltyMatrix
```
public double[][][] _penaltyMatrix
```
  - _gamColnames
```
public java.lang.String[][] _gamColnames
```
  - _gamColIndices
```
public int[][] _gamColIndices
```
  - _betaInfo
```
public GLM.BetaInfo _betaInfo
```
  - WORK_TOTAL
```
protected static final long WORK_TOTAL
```
    See Also:
    
    Constant Field Values
- Constructor Detail
  - GLM
```
public GLM(boolean startup_once)
```
  - GLM
```
public GLM(GLMModel.GLMParameters parms)
```
  - GLM
```
public GLM(GLMModel.GLMParameters parms,
           double[][][] penaltyMatrix,
           java.lang.String[][] gamColnames)
```
    This constructor is only called by GAM when it is trying to build a GAM model using GLM. Internal function, DO NOT USE.
  - GLM
```
public GLM(GLMModel.GLMParameters parms,
           water.Key dest)
```
- Method Detail
  - isSupervised
```
public boolean isSupervised()
```
    Specified by:
    
    isSupervised in class hex.ModelBuilder<GLMModel,GLMModel.GLMParameters,GLMModel.GLMOutput>
  - can_build
```
public hex.ModelCategory[] can_build()
```
    Specified by:
    
    can_build in class hex.ModelBuilder<GLMModel,GLMModel.GLMParameters,GLMModel.GLMOutput>
  - havePojo
```
public boolean havePojo()
```
    Overrides:
    
    havePojo in class hex.ModelBuilder<GLMModel,GLMModel.GLMParameters,GLMModel.GLMOutput>
  - haveMojo
```
public boolean haveMojo()
```
    Overrides:
    
    haveMojo in class hex.ModelBuilder<GLMModel,GLMModel.GLMParameters,GLMModel.GLMOutput>
  - computeCrossValidation
```
public void computeCrossValidation()
```
    GLM implementation of N-fold cross-validation. We need to compute the sequence of lambdas for the main model so the folds share the same lambdas. We also want to set the _cv flag so that the dependent jobs know they're being run withing CV (so e.g. they do not unlock the models in the end)
    
    Overrides:
    
    computeCrossValidation in class hex.ModelBuilder<GLMModel,GLMModel.GLMParameters,GLMModel.GLMOutput>
  - cv_computeAndSetOptimalParameters
```
public void cv_computeAndSetOptimalParameters(hex.ModelBuilder[] cvModelBuilders)
```
    If run with lambda search, we need to take extra action performed after cross-val models are built. Each of the folds have been computed with ots own private validation dataset and it performed early stopping based on it. => We need to: 1. compute cross-validated lambda estimate 2. set the lambda estimate to all n-folds models (might require extra model fitting if the particular model stopped too early!) 3. compute cross-validated scoring history (cross-validated deviance standard error per lambda) 4. unlock the n-folds models (they are changed here, so the unlocking happens here)
    
    Overrides:
    
    cv_computeAndSetOptimalParameters in class hex.ModelBuilder<GLMModel,GLMModel.GLMParameters,GLMModel.GLMOutput>
  - findIterIndexAcrossFolds
```
public static int[] findIterIndexAcrossFolds(java.util.List<java.lang.Integer>[] cvModelIters,
                                             int fold0Index)
```
    This method is used to locate common iteration indices across all folds. Since scoring history is scored by user specifying the scoring interval and by a time interval determined by system computation speed, there can be scoring history with different scoring indices across folds. This method is used to find the commen iteration indices and return it.
    
    Parameters:
    
    cvModelIters: - store model keys from models generated by cross validation.
    
    fold0Index: - iteration index of fold 0 model
  - checkMemoryFootPrint
```
protected void checkMemoryFootPrint(DataInfo activeData)
```
  - nclasses
```
public int nclasses()
```
    Overrides:
    
    nclasses in class hex.ModelBuilder<GLMModel,GLMModel.GLMParameters,GLMModel.GLMOutput>
  - computePriorClassDistribution
```
protected boolean computePriorClassDistribution()
```
    Overrides:
    
    computePriorClassDistribution in class hex.ModelBuilder<GLMModel,GLMModel.GLMParameters,GLMModel.GLMOutput>
  - init
```
public void init(boolean expensive)
```
    Overrides:
    
    init in class hex.ModelBuilder<GLMModel,GLMModel.GLMParameters,GLMModel.GLMOutput>
  - setHGLMInitValues
```
public void setHGLMInitValues(double[] beta)
```
    initialize the following parameters for HGLM from either user initial inputs or from a GLM model if user did not provide any starting values. If user initial inputs are provided, it should be in the form of a big double array and the values should be stacked according to the following sequence: - beta, ubeta, phi, psi, tau, init_sig_e, init_sig_u
    
    Parameters:
    
    beta - Internal H2O method. Do not use.
  - restrictMag
```
public double restrictMag(double val)
```
  - copyUserInitialValues
```
public void copyUserInitialValues(int fixedEffectSize,
                                  int randomEffectSize,
                                  double[] beta,
                                  double[] ubeta,
                                  double[] phi,
                                  double hlcorrection,
                                  double[] psi,
                                  water.fvec.Frame randWeights,
                                  java.lang.String[] randCoeffNames)
```
    This method performs a simple copying of user provided initial values to parameters - beta, ubeta, phi, tau, psi, init_sig_u
  - trainModelImpl
```
protected GLM.GLMDriver trainModelImpl()
```
    Specified by:
    
    trainModelImpl in class hex.ModelBuilder<GLMModel,GLMModel.GLMParameters,GLMModel.GLMOutput>
  - COD_solve
```
public double[] COD_solve(ComputationState.GramXY gram,
                          double alpha,
                          double lambda)
```
  - sparseOffset
```
protected static double sparseOffset(double[] beta,
                                     DataInfo dinfo)
```

Class GLM

Nested Class Summary

Nested classes/interfaces inherited from class hex.ModelBuilder

Field Summary

Fields inherited from class hex.ModelBuilder

Constructor Summary

Method Summary

Methods inherited from class hex.ModelBuilder

Methods inherited from class water.Iced

Methods inherited from class java.lang.Object

Field Detail

SCORING_INTERVAL_MSEC

_randC

_generatedWeights

_randCoeffNames

_randomColNames

_penaltyMatrix

_gamColnames

_gamColIndices

_betaInfo

WORK_TOTAL

Constructor Detail

GLM

GLM

GLM

GLM

Method Detail

isSupervised

can_build

havePojo

haveMojo

computeCrossValidation

cv_computeAndSetOptimalParameters

findIterIndexAcrossFolds

checkMemoryFootPrint

nclasses

computePriorClassDistribution

init

setHGLMInitValues

restrictMag

copyUserInitialValues

trainModelImpl

COD_solve

sparseOffset