water.bindings.pojos

Class NaiveBayesParametersV3

java.lang.Object

water.bindings.pojos.Schema

water.bindings.pojos.ModelParametersSchema

water.bindings.pojos.NaiveBayesParametersV3

public class NaiveBayesParametersV3
extends ModelParametersSchema

Field Summary

Fields

Modifier and Type	Field and Description
boolean	balance_classes Balance training data class counts via over/under-sampling (for imbalanced data).
float[]	class_sampling_factors Desired over/under-sampling ratios per class (in lexicographic order).
boolean	compute_metrics Compute metrics on training data
double	eps_prob Cutoff below which probability is replaced with min_prob
double	eps_sdev Cutoff below which standard deviation is replaced with min_sdev
double	laplace Laplace smoothing parameter
float	max_after_balance_size Maximum relative size of the training data after balancing class counts (can be less than 1.0).
int	max_confusion_matrix_size Maximum size (# classes) for confusion matrices to be printed in the Logs
int	max_hit_ratio_k Max.
double	min_prob Min.
double	min_sdev Min.
long	seed Seed for pseudo random number generator (only used for cross-validation and fold_assignment="Random" or "AUTO")

Fields inherited from class water.bindings.pojos.ModelParametersSchema

checkpoint, fold_assignment, fold_column, ignore_const_cols, ignored_columns, keep_cross_validation_fold_assignment, keep_cross_validation_predictions, max_runtime_secs, model_id, nfolds, offset_column, parallelize_cross_validation, response_column, score_each_iteration, stopping_metric, stopping_rounds, stopping_tolerance, training_frame, validation_frame, weights_column

Constructor Summary

Constructors

Constructor and Description
NaiveBayesParametersV3()

Method Summary

Methods

Modifier and Type	Method and Description
java.lang.String	toString() Return the contents of this object as a JSON String.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

balance_classes

public boolean balance_classes

Balance training data class counts via over/under-sampling (for imbalanced data).

class_sampling_factors

public float[] class_sampling_factors

Desired over/under-sampling ratios per class (in lexicographic order). If not specified, sampling factors will be automatically computed to obtain class balance during training. Requires balance_classes.

max_after_balance_size

public float max_after_balance_size

Maximum relative size of the training data after balancing class counts (can be less than 1.0). Requires balance_classes.

max_confusion_matrix_size

public int max_confusion_matrix_size

Maximum size (# classes) for confusion matrices to be printed in the Logs

max_hit_ratio_k

public int max_hit_ratio_k

Max. number (top K) of predictions to use for hit ratio computation (for multi-class only, 0 to disable)

laplace

public double laplace

Laplace smoothing parameter

min_sdev

public double min_sdev

Min. standard deviation to use for observations with not enough data

eps_sdev

public double eps_sdev

Cutoff below which standard deviation is replaced with min_sdev

min_prob

public double min_prob

Min. probability to use for observations with not enough data

eps_prob

public double eps_prob

Cutoff below which probability is replaced with min_prob

compute_metrics

public boolean compute_metrics

Compute metrics on training data

seed

public long seed

Seed for pseudo random number generator (only used for cross-validation and fold_assignment="Random" or "AUTO")

Constructor Detail

NaiveBayesParametersV3

public NaiveBayesParametersV3()

Method Detail

toString

public java.lang.String toString()

Return the contents of this object as a JSON String.

Overrides:

toString in class ModelParametersSchema