public static final class IsolationForestV3.IsolationForestParametersV3 extends SharedTreeV3.SharedTreeParametersV3<IsolationForestModel.IsolationForestParameters,IsolationForestV3.IsolationForestParametersV3>
| Modifier and Type | Field and Description |
|---|---|
static java.lang.String[] |
fields |
int |
mtries |
double |
sample_rate |
long |
sample_size |
balance_classes, build_tree_one_node, calibrate_model, calibration_frame, check_constant_response, class_sampling_factors, col_sample_rate_change_per_level, col_sample_rate_per_tree, histogram_type, max_after_balance_size, max_confusion_matrix_size, max_depth, max_hit_ratio_k, min_rows, min_split_improvement, nbins, nbins_cats, nbins_top_level, ntrees, r2_stopping, sample_rate_per_class, score_tree_interval, seedcategorical_encoding, checkpoint, custom_distribution_func, custom_metric_func, distribution, export_checkpoints_dir, fold_assignment, fold_column, huber_alpha, ignore_const_cols, ignored_columns, keep_cross_validation_fold_assignment, keep_cross_validation_models, 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 |
|---|
IsolationForestParametersV3() |
append_field_arrays, fields, fillFromImpl, fillImpl, writeParametersJSONcreateAndFillImpl, createImpl, extractVersionFromSchemaName, fillFromBody, fillFromImpl, fillFromImpl, fillFromParms, fillFromParms, fillImpl, getImplClass, getImplClass, getSchemaName, getSchemaType, getSchemaVersion, init_meta, markdown, markdown, newInstance, newInstance, setField, setSchemaType_doNotCallpublic static java.lang.String[] fields
@API(help="Number of randomly sampled observations used to train each Isolation Forest tree. Only one of parameters sample_size and sample_rate should be defined. If sample_rate is defined, sample_size will be ignored.",
gridable=true)
public long sample_size
@API(help="Rate of randomly sampled observations used to train each Isolation Forest tree. Needs to be in range from 0.0 to 1.0. If set to -1, sample_rate is disabled and sample_size will be used instead.",
gridable=true)
public double sample_rate
@API(help="Number of variables randomly sampled as candidates at each split. If set to -1, defaults (number of predictors)/3.",
gridable=true)
public int mtries