public static final class AggregatorV99.AggregatorParametersV99 extends water.api.schemas3.ModelParametersSchemaV3<AggregatorModel.AggregatorParameters,AggregatorV99.AggregatorParametersV99>
Modifier and Type | Field and Description |
---|---|
static java.lang.String[] |
fields |
int |
k |
int |
max_iterations |
PCAModel.PCAParameters.Method |
pca_method |
double |
rel_tol_num_exemplars |
long |
seed |
int |
target_num_exemplars |
DataInfo.TransformType |
transform |
boolean |
use_all_factor_levels |
categorical_encoding, checkpoint, distribution, fold_assignment, fold_column, huber_alpha, ignore_const_cols, ignored_columns, keep_cross_validation_fold_assignment, keep_cross_validation_predictions, max_categorical_levels, max_runtime_secs, model_id, nfolds, offset_column, parallelize_cross_validation, quantile_alpha, response_column, score_each_iteration, stopping_metric, stopping_rounds, stopping_tolerance, training_frame, tweedie_power, validation_frame, weights_column
Constructor and Description |
---|
AggregatorV99.AggregatorParametersV99() |
append_field_arrays, fields, fillFromImpl, fillImpl, writeParametersJSON
createAndFillImpl, createImpl, extractVersionFromSchemaName, fillFromImpl, fillFromImpl, fillFromParms, fillFromParms, fillImpl, getImplClass, getImplClass, getSchemaName, getSchemaType, getSchemaVersion, init_meta, markdown, markdown, newInstance, newInstance, setField, setSchemaType_doNotCall
public static java.lang.String[] fields
@API(help="Transformation of training data", values={"NONE","STANDARDIZE","NORMALIZE","DEMEAN","DESCALE"}, gridable=true, level=expert) public DataInfo.TransformType transform
@API(help="Method for computing PCA (Caution: GLRM is currently experimental and unstable)", values={"GramSVD","Power","Randomized","GLRM"}, gridable=true, level=expert) public PCAModel.PCAParameters.Method pca_method
@API(help="Rank of matrix approximation", direction=INOUT, gridable=true, level=secondary) public int k
@API(help="Maximum number of iterations for PCA", direction=INOUT, gridable=true, level=expert) public int max_iterations
@API(help="Targeted number of exemplars", direction=INOUT, gridable=true, level=secondary) public int target_num_exemplars
@API(help="Relative tolerance for number of exemplars (e.g, 0.5 is +/- 50%)", direction=INOUT, gridable=true, level=secondary) public double rel_tol_num_exemplars
@API(help="RNG seed for initialization", direction=INOUT, level=secondary) public long seed
@API(help="Whether first factor level is included in each categorical expansion", direction=INOUT, level=expert) public boolean use_all_factor_levels