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oracle.dmt.jdm.supervised.classification
Class OraLift

java.lang.Object
oracle.dmt.jdm.OraDMObject
oracle.dmt.jdm.supervised.classification.OraLift

All Implemented Interfaces:

javax.datamining.supervised.classification.Lift, oracle.dmt.jdm.OraPLSQLConstants

public class OraLift

extends oracle.dmt.jdm.OraDMObject

implements javax.datamining.supervised.classification.Lift

OraLift is an oracle extension to javax.datamining.supervised.classification.Lift class. This class adds following new get methods to support getting lift details as arrays and also supports count values as double values.

• getLift(): returns double[]
• getCumulativeLift(): returns double[]
• getCases(): returns double[]
• getNumberOfPositiveCases(): returns double[]
• getNumberOfNegativeCases(): returns double[]
• getPercentageSize(): returns double[]
• getTargetDensity(): returns double[]
• getCumulativeTargetDensity(): returns double[]
• getProbabilityOrCostThreshold(): returns double[]
• getCumulativeGain(): returns double[]

See Also:

Lift

Field Summary

Fields inherited from interface oracle.dmt.jdm.OraPLSQLConstants

abns_max_build_minutes, abns_max_nb_predictors, abns_max_predictors, abns_model_type, abns_multi_feature, abns_naive_bayes, abns_single_feature, algo_adaptive_bayes_network, algo_ai_mdl, algo_ai_mdl2, algo_apriori_association_rules, algo_decision_tree, algo_generalized_linear_model, algo_kmeans, algo_naive_bayes, algo_name, algo_nonnegative_matrix_factor, algo_ocluster, algo_predictor_variance, algo_support_vector_machines, apply_cost_content, apply_lower_content, apply_nodeid_content, apply_pred_value_content, apply_probability_content, apply_upper_content, asso_max_rule_length, asso_min_confidence, asso_min_support, association, association_in_model, attribute_importance, clas_cost_table_name, clas_priors_table_name, clas_weights_table_name, classification, clus_num_clusters, clustering, feat_num_features, feature_extraction, glms_conf_level, glms_conf_level_default, glms_diagnostics_table_name, glms_reference_class_name, glms_ridge_reg_disable, glms_ridge_reg_enable, glms_ridge_regression, glms_ridge_value, glms_vif_for_ridge, glms_vif_ridge_disable, glms_vif_ridge_enable, kmns_block_growth, kmns_conv_tolerance, kmns_cosine, kmns_distance, kmns_euclidean, kmns_fast_cosine, kmns_iterations, kmns_min_pct_attr_support, kmns_num_bins, kmns_size, kmns_split_criterion, kmns_variance, nabs_pairwise_threshold, nabs_singleton_threshold, nmfs_conv_tolerance, nmfs_num_iterations, nmfs_random_seed, ocluster_max_buffer, ocluster_sensitivity, odms_missing_value_delete_row, odms_missing_value_mean_mode, odms_missing_value_treatment, odms_row_weight_column_name, operator_equal, operator_equal_v, operator_greater_or_equal, operator_greater_or_equal_v, operator_greater_than, operator_greater_than_v, operator_in, operator_in_v, operator_less_or_equal, operator_less_or_equal_v, operator_less_than, operator_less_than_v, operator_not_equal, operator_not_equal_v, operator_not_in, operator_not_in_v, oracle_char_type, oracle_dm_nested_categoricals, oracle_dm_nested_numericals, oracle_float_type, oracle_number_type, oracle_varchar2_type, prep_auto, prep_auto_off, prep_auto_on, regression, svms_active_learning, svms_al_disable, svms_al_enable, svms_complexity_factor, svms_conv_tolerance, svms_epsilon, svms_gaussian, svms_kernel_cache_size, svms_kernel_function, svms_linear, svms_outlier_rate, svms_std_dev, tree_impurity_entropy, tree_impurity_gini, tree_impurity_metric, tree_impurity_metric_default, tree_term_max_depth, tree_term_max_depth_default, tree_term_max_depth_max, tree_term_max_depth_min, tree_term_max_surrogates_max, tree_term_max_surrogates_min, tree_term_minpct_node, tree_term_minpct_node_default, tree_term_minpct_node_max, tree_term_minpct_split, tree_term_minpct_split_default, tree_term_minpct_split_max, tree_term_minrec_node, tree_term_minrec_node_default, tree_term_minrec_split, tree_term_minrec_split_default

Method Summary

double[]	getCases() Returns an array containing the number of cases per quantile.
double[]	getCumulativeGain() Returns an array containing the gain per quantile.
double[]	getCumulativeLift() Returns an array containing the cumulative lift values of the quantile.
double[]	getCumulativeTargetDensity() Returns an array containing the cumulative target density per quantile.
double[]	getLift() Returns an array containing the lift values per quantile.
double[]	getNumberOfNegativeCases() Returns an array containing the number of negative cases per quantile.
double[]	getNumberOfPositiveCases() Returns an array containing the number of positive cases per quantile.
double[]	getPercentageSize() Returns an array containing the percentage size per quantile.
double[]	getProbabilityOrCostThreshold() Returns an array containing the probability/cost threshold per quantile.
double[]	getTargetDensity() Returns an array containing the target density per quantile.

Methods inherited from class oracle.dmt.jdm.OraDMObject

createException, createException, createRuntimeException, createRuntimeException, getLocalizedMessage, isConnectionOpen, logInfo, logSevere, logTrace, logTrace, unsupported, unsupported

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Detail

getLift

public double[] getLift()

Returns an array containing the lift values per quantile. Array element 0 contains the first quantile. Array element N-1 contains the last quantile, where N is the number of quantiles. Lift of a quantile is the ratio of the number of positive cases in the quantile and average number of positive cases per quantile in the test dataset.

Returns:

double[]

Since:

OJDM 11.1.0.0

getCumulativeLift

public double[] getCumulativeLift()

Returns an array containing the cumulative lift values of the quantile. Array element 0 contains the first quantile. Array element N-1 contains the last quantile, where N is the number of quantiles. Cumulative lift for quantile n is the ratio of number of positive cases in the first n quantiles and the average number of positive cases in the first n quantiles.

Returns:

double[]

Since:

OJDM 11.1.0.0

getCases

public double[] getCases()

Returns an array containing the number of cases per quantile. Array element 0 contains the first quantile. Array element N-1 contains the last quantile, where N is the number of quantiles.

Returns:

double[]

Since:

OJDM 11.1.0.0

getNumberOfPositiveCases

public double[] getNumberOfPositiveCases()

Returns an array containing the number of positive cases per quantile. Array element 0 contains the first quantile. Array element N-1 contains the last quantile, where N is the number of quantiles.

Returns:

double[]

Since:

OJDM 11.1.0.0

getNumberOfNegativeCases

public double[] getNumberOfNegativeCases()

Returns an array containing the number of negative cases per quantile. Array element 0 contains the first quantile. Array element N-1 contains the last quantile, where N is the number of quantiles.

Returns:

double[]

Since:

OJDM 11.1.0.0

getPercentageSize

public double[] getPercentageSize()

Returns an array containing the percentage size per quantile. Array element 0 contains the first quantile. Array element N-1 contains the last quantile, where N is the number of quantiles. Percentage size is the ratio of the number of cases in the quantile and total number of cases in the test dataset. The range of percentage value is between 0 and 100.

Returns:

double[]

Since:

OJDM 11.1.0.0

getTargetDensity

public double[] getTargetDensity()

Returns an array containing the target density per quantile. Array element 0 contains the first quantile. Array element N-1 contains the last quantile, where N is the number of quantiles. Target density of a quantile is the number of true positive cases in that quantile divided by the total number of cases in the quantile.

Returns:

double[]

Since:

OJDM 11.1.0.0

getCumulativeTargetDensity

public double[] getCumulativeTargetDensity()

Returns an array containing the cumulative target density per quantile. Array element 0 contains the first quantile. Array element N-1 contains the last quantile, where N is the number of quantiles. Cumulative target density for quantile n is the target density computed over the first n quantiles. i.e., the ratio of the number of positive cases over the first n quantiles and total number of cases over the first n quantiles.

Returns:

double[]

Since:

OJDM 11.1.0.0

getProbabilityOrCostThreshold

public double[] getProbabilityOrCostThreshold()

Returns an array containing the probability/cost threshold per quantile. Array element 0 contains the first quantile. Array element N-1 contains the last quantile, where N is the number of quantiles. Probability threshold for a quantile n is the minimum probability for the positive target to be included in this quantile or any preceding quantiles (quantiles n-1, n-2,..., 1). If a cost matrix is used, a cost threshold is reported instead. The cost threshold is the maximum cost for the positive target to be included in this quantile or any of the preceding quantiles.

Returns:

double[]

Since:

OJDM 11.1.0.0

getCumulativeGain

public double[] getCumulativeGain()

Returns an array containing the gain per quantile. Array element 0 contains the first quantile. Array element N-1 contains the last quantile, where N is the number of quantiles. Cumulative gain for a given quantile is the ratio of the cumulative number of positive cases to the total number of positive cases in the test dataset.

Returns:

double[]

Since:

OJDM 11.1.0.0

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