public class PCAParametersV3 extends ModelParametersSchemaV3
| Modifier and Type | Field and Description |
|---|---|
boolean |
computeMetrics
Whether to compute metrics on the training data
|
boolean |
imputeMissing
Whether to impute missing entries with the column mean
|
int |
k
Rank of matrix approximation
|
int |
maxIterations
Maximum training iterations
|
PCAMethod |
pcaMethod
Method for computing PCA (Caution: Power and GLRM are currently experimental and unstable)
|
long |
seed
RNG seed for initialization
|
DataInfoTransformType |
transform
Transformation of training data
|
boolean |
useAllFactorLevels
Whether first factor level is included in each categorical expansion
|
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 |
|---|
PCAParametersV3()
Public constructor
|
| Modifier and Type | Method and Description |
|---|---|
java.lang.String |
toString()
Return the contents of this object as a JSON String.
|
public DataInfoTransformType transform
public PCAMethod pcaMethod
public int k
public int maxIterations
public long seed
public boolean useAllFactorLevels
public boolean computeMetrics
public boolean imputeMissing
public java.lang.String toString()
toString in class ModelParametersSchemaV3