public final class GLM.GLMDriver extends water.H2O.H2OCountedCompleter<hex.ModelBuilder.Driver> implements L_BFGS.ProgressMonitor
| Constructor and Description |
|---|
GLMDriver() |
| Modifier and Type | Method and Description |
|---|---|
void |
addWdataZiEtaOld2Response()
Internal H2O method.
|
GLMModel |
buildGammaGLM(water.fvec.Frame returnFrame,
water.fvec.Frame constXYWeight,
int[] devHvColIdx,
long startRowIndex,
long numRows,
boolean computePValues)
This method will generate a training frame according to HGLM doc, build a gamma GLM model with dispersion
factor set to 1 if enabled and calcluate the p-value if enabled.
|
double[] |
calculate_all_beta(double[] start_delta,
water.fvec.Frame augXZ,
water.fvec.Frame augZW,
int totRandCatLevels,
double[][] cholRcopy)
This method will estimate beta and ubeta using QR decomposition.
|
GLMTask.CalculateW4Data |
calculateNewWAugXZ(water.fvec.Frame augXZ,
int[] randCatLevels) |
void |
computeImpl() |
protected GLMModel.Submodel |
computeSubmodel(int i,
double lambda,
double nullDevTrain,
double nullDevValid) |
void |
copyOver(double[][] cholR,
double[][] cholRcopy) |
GLMModel |
fitDataDispersion(water.fvec.Frame returnFrame,
int[] devHvColIdx,
double[] VC1)
This method estimates the init_sig_e by building a gamma GLM with response
|
double[] |
lfv_du_dv(GLMModel.GLMParameters.Family[] family,
GLMModel.GLMParameters.Link[] link,
double[] phi,
double[] u) |
water.fvec.Frame |
makeZeroOrOneFrame(long rowNumber,
int colNumber,
int val,
java.lang.String[] columnNames) |
void |
onCompletion(jsr166y.CountedCompleter caller) |
boolean |
onExceptionalCompletion(java.lang.Throwable t,
jsr166y.CountedCompleter caller) |
boolean |
progress(double[] beta,
double likelihood) |
boolean |
progress(double[] beta,
OptimizationUtils.GradientInfo ginfo) |
boolean |
progressHGLMGLMMME(double sumDiff2,
double sumeta2,
int iteration,
boolean atGLMMME,
GLMModel fixedModel,
GLMModel[] randModels,
water.fvec.Frame glmmmeReturns,
water.fvec.Frame hvDataOnly,
double[] VC1,
double[][] VC2,
double[][] cholR,
water.fvec.Frame augZ) |
protected void |
updateProgress(boolean canScore) |
protected void |
updateProgress(GLMModel fixedModel,
GLMModel[] randModels,
water.fvec.Frame glmmmeReturns,
water.fvec.Frame hvDataOnly,
double[] VC1,
double[][] VC2,
double sumDiff2,
double convergence,
boolean canScore,
double[][] cholR,
water.fvec.Frame augXZ) |
asBytes, clone, compute, compute1, currThrPriority, frozenType, icer, priority, read, readJSON, reloadFromBytes, write, writeJSON__tryComplete, addToPendingCount, compareAndSetPendingCount, complete, exec, getCompleter, getPendingCount, getRawResult, setCompleter, setPendingCount, setRawResult, tryCompleteadapt, adapt, adapt, cancel, compareAndSetForkJoinTaskTag, completeExceptionally, fork, get, get, getException, getForkJoinTaskTag, getPool, getQueuedTaskCount, getSurplusQueuedTaskCount, helpQuiesce, inForkJoinPool, invoke, invokeAll, invokeAll, invokeAll, isCancelled, isCompletedAbnormally, isCompletedNormally, isDone, join, peekNextLocalTask, pollNextLocalTask, pollTask, quietlyComplete, quietlyInvoke, quietlyJoin, reinitialize, setForkJoinTaskTag, tryUnforkpublic water.fvec.Frame makeZeroOrOneFrame(long rowNumber,
int colNumber,
int val,
java.lang.String[] columnNames)
public GLMTask.CalculateW4Data calculateNewWAugXZ(water.fvec.Frame augXZ, int[] randCatLevels)
public void copyOver(double[][] cholR,
double[][] cholRcopy)
public double[] calculate_all_beta(double[] start_delta,
water.fvec.Frame augXZ,
water.fvec.Frame augZW,
int totRandCatLevels,
double[][] cholRcopy)
start_delta - augXZ - augZW - totRandCatLevels - cholRcopy - public GLMModel fitDataDispersion(water.fvec.Frame returnFrame, int[] devHvColIdx, double[] VC1)
returnFrame - devHvColIdx - VC1 - public GLMModel buildGammaGLM(water.fvec.Frame returnFrame, water.fvec.Frame constXYWeight, int[] devHvColIdx, long startRowIndex, long numRows, boolean computePValues)
returnFrame - constXYWeight - devHvColIdx - startRowIndex - numRows - computePValues - public double[] lfv_du_dv(GLMModel.GLMParameters.Family[] family, GLMModel.GLMParameters.Link[] link, double[] phi, double[] u)
protected GLMModel.Submodel computeSubmodel(int i, double lambda, double nullDevTrain, double nullDevValid)
public void computeImpl()
public void addWdataZiEtaOld2Response()
public void onCompletion(jsr166y.CountedCompleter caller)
public boolean onExceptionalCompletion(java.lang.Throwable t,
jsr166y.CountedCompleter caller)
public boolean progress(double[] beta,
OptimizationUtils.GradientInfo ginfo)
progress in interface L_BFGS.ProgressMonitorpublic boolean progressHGLMGLMMME(double sumDiff2,
double sumeta2,
int iteration,
boolean atGLMMME,
GLMModel fixedModel,
GLMModel[] randModels,
water.fvec.Frame glmmmeReturns,
water.fvec.Frame hvDataOnly,
double[] VC1,
double[][] VC2,
double[][] cholR,
water.fvec.Frame augZ)
public boolean progress(double[] beta,
double likelihood)
protected void updateProgress(GLMModel fixedModel, GLMModel[] randModels, water.fvec.Frame glmmmeReturns, water.fvec.Frame hvDataOnly, double[] VC1, double[][] VC2, double sumDiff2, double convergence, boolean canScore, double[][] cholR, water.fvec.Frame augXZ)
protected void updateProgress(boolean canScore)