public class GLMParametersV3 extends ModelParametersSchemaV3
| Modifier and Type | Field and Description |
|---|---|
double[] |
alpha
distribution of regularization between L1 and L2.
|
boolean |
balanceClasses
Balance training data class counts via over/under-sampling (for imbalanced data).
|
FrameKeyV3 |
betaConstraints
beta constraints
|
double |
betaEpsilon
converge if beta changes less (using L-infinity norm) than beta esilon, ONLY applies to IRLSM solver
|
float[] |
classSamplingFactors
Desired over/under-sampling ratios per class (in lexicographic order).
|
boolean |
computePValues
request p-values computation, p-values work only with IRLSM solver and no regularization
|
boolean |
earlyStopping
stop early when there is no more relative improvement on train or validation (if provided)
|
GLMFamily |
family
Family.
|
double |
gradientEpsilon
Converge if objective changes less (using L-infinity norm) than this, ONLY applies to L-BFGS solver.
|
java.lang.String[] |
interactions
A list of predictor column indices to interact.
|
boolean |
intercept
include constant term in the model
|
double[] |
lambda
regularization strength
|
double |
lambdaMinRatio
Min lambda used in lambda search, specified as a ratio of lambda_max.
|
boolean |
lambdaSearch
use lambda search starting at lambda max, given lambda is then interpreted as lambda min
|
GLMLink |
link |
int |
maxActivePredictors
Maximum number of active predictors during computation.
|
float |
maxAfterBalanceSize
Maximum relative size of the training data after balancing class counts (can be less than 1.0).
|
int |
maxConfusionMatrixSize
[Deprecated] Maximum size (# classes) for confusion matrices to be printed in the Logs
|
int |
maxHitRatioK
Max.
|
int |
maxIterations
Maximum number of iterations
|
DeepLearningMissingValuesHandling |
missingValuesHandling
Handling of missing values.
|
int |
nlambdas
Number of lambdas to be used in a search.
|
boolean |
nonNegative
Restrict coefficients (not intercept) to be non-negative
|
double |
objectiveEpsilon
Converge if objective value changes less than this.
|
double |
objReg
likelihood divider in objective value computation, default is 1/nobs
|
double |
prior
prior probability for y==1.
|
boolean |
removeCollinearColumns
in case of linearly dependent columns remove some of the dependent columns
|
long |
seed
Seed for pseudo random number generator (if applicable)
|
GLMSolver |
solver
AUTO will set the solver based on given data and the other parameters.
|
boolean |
standardize
Standardize numeric columns to have zero mean and unit variance
|
double |
tweedieLinkPower
Tweedie link power
|
double |
tweedieVariancePower
Tweedie variance power
|
categoricalEncoding, checkpoint, distribution, foldAssignment, foldColumn, huberAlpha, ignoreConstCols, ignoredColumns, keepCrossValidationFoldAssignment, keepCrossValidationPredictions, maxRuntimeSecs, modelId, nfolds, offsetColumn, parallelizeCrossValidation, quantileAlpha, responseColumn, scoreEachIteration, stoppingMetric, stoppingRounds, stoppingTolerance, trainingFrame, tweediePower, validationFrame, weightsColumn| Constructor and Description |
|---|
GLMParametersV3()
Public constructor
|
| Modifier and Type | Method and Description |
|---|---|
java.lang.String |
toString()
Return the contents of this object as a JSON String.
|
public long seed
public GLMFamily family
public double tweedieVariancePower
public double tweedieLinkPower
public GLMSolver solver
public double[] alpha
public double[] lambda
public boolean lambdaSearch
public boolean earlyStopping
public int nlambdas
public boolean standardize
public DeepLearningMissingValuesHandling missingValuesHandling
public boolean nonNegative
public int maxIterations
public double betaEpsilon
public double objectiveEpsilon
public double gradientEpsilon
public double objReg
public GLMLink link
public boolean intercept
public double prior
public double lambdaMinRatio
public FrameKeyV3 betaConstraints
public int maxActivePredictors
public java.lang.String[] interactions
public boolean balanceClasses
public float[] classSamplingFactors
public float maxAfterBalanceSize
public int maxConfusionMatrixSize
public int maxHitRatioK
public boolean computePValues
public boolean removeCollinearColumns
public java.lang.String toString()
toString in class ModelParametersSchemaV3