public static final class PCAV99.PCAParametersV99 extends water.api.ModelParametersSchema<PCAModel.PCAParameters,PCAV99.PCAParametersV99>
| Modifier and Type | Field and Description |
|---|---|
int |
k |
java.lang.String |
loading_name |
int |
max_iterations |
static java.lang.String[] |
own_fields |
PCAModel.PCAParameters.Method |
pca_method |
long |
seed |
DataInfo.TransformType |
transform |
boolean |
use_all_factor_levels |
| Constructor and Description |
|---|
PCAV99.PCAParametersV99() |
append_field_arrays, fields, fillFromImpl, fillImpl, writeParametersJSONacceptsFrame, createAndFillImpl, createImpl, extractVersion, fillFromParms, getExperimentalVersion, getHighestSupportedVersion, getImplClass, getImplClass, getLatestVersion, getSchemaVersion, markdown, markdown, markdown, markdown, newInstance, register, registerAllSchemasIfNecessary, schema, schema, schema, schema, schema, schemaClass, schemaClass, schemaClass, schemaClass, schemaspublic static java.lang.String[] own_fields
@API(help="Transformation of training data",
values={"NONE","STANDARDIZE","NORMALIZE","DEMEAN","DESCALE"})
public DataInfo.TransformType transform
@API(help="Method for computing PCA",
values={"GramSVD","Power","GLRM"})
public PCAModel.PCAParameters.Method pca_method
@API(help="Rank of matrix approximation",
required=true,
direction=INOUT)
public int k
@API(help="Maximum training iterations",
direction=INOUT)
public int max_iterations
@API(help="RNG seed for initialization",
direction=INOUT)
public long seed
@API(help="Frame key to save left singular vectors from SVD",
direction=INPUT)
public java.lang.String loading_name
@API(help="Whether first factor level is included in each categorical expansion",
direction=INOUT)
public boolean use_all_factor_levels