oracle.dmt.jdm.supervised.regression
Class OraRegressionTestMetrics

java.lang.Object
oracle.dmt.jdm.OraDMObject
oracle.dmt.jdm.OraMiningObject
oracle.dmt.jdm.supervised.OraTestMetrics
oracle.dmt.jdm.supervised.regression.OraRegressionTestMetrics

All Implemented Interfaces:

javax.datamining.MiningObject, oracle.dmt.jdm.OraPLSQLConstants, javax.datamining.supervised.regression.RegressionTestMetrics, javax.datamining.supervised.TestMetrics

public class OraRegressionTestMetrics

extends oracle.dmt.jdm.supervised.OraTestMetrics

implements javax.datamining.supervised.regression.RegressionTestMetrics

OraRegressionTestMetrics provides set and get methods to specify the target attribute normalization details. If user specifies target attribute normalization details, it will be used to denormalize the test metrics values.

See Also:

MiningObject, OraMiningObject, TestMetrics, OraTestMetrics, RegressionTestMetrics

Field Summary

Fields inherited from class oracle.dmt.jdm.OraMiningObject

DESCRIPTION_DELIMITER

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_kmeans, algo_naive_bayes, algo_name, algo_nonnegative_matrix_factor, algo_ocluster, algo_predictor_variance, algo_support_vector_machines, apply_cost_content, apply_nodeid_content, apply_pred_value_content, apply_probability_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, classification, clus_num_clusters, clustering, feat_num_features, feature_extraction, 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, 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, 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

java.lang.Double	getTargetNormalizationScaleValue() Returns the specified normalization scale value of the target column.
java.lang.Double	getTargetNormalizationShiftValue() Returns the specified normalization shift value of the target column.
void	setTargetNormalizationDetails(java.lang.Double shiftValue, java.lang.Double scaleValue) Sets the normalization details of the target columns.

Methods inherited from class oracle.dmt.jdm.supervised.OraTestMetrics

doesObjectExistInDatabase, getModelName, getObjectType, getTaskIdentifier, getTestDataName, isInputObject, removeObjectFromDatabase, renameObjectInDatabase, retrieveObjectFromDatabase, retrieveObjectFromDatabaseByID, retrieveObjectsFromDatabase

Methods inherited from class oracle.dmt.jdm.OraMiningObject

doBeforeStore, getCreationDate, getCreatorInfo, getDescription, getName, getObjectIdentifier, saveObjectInDatabase, setDescription

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

Methods inherited from interface javax.datamining.supervised.TestMetrics

getModelName, getTaskIdentifier, getTestDataName

Methods inherited from interface javax.datamining.MiningObject

getCreationDate, getCreatorInfo, getDescription, getName, getObjectIdentifier, getObjectType, setDescription

Method Detail

setTargetNormalizationDetails

public void setTargetNormalizationDetails(java.lang.Double shiftValue,
                                          java.lang.Double scaleValue)

Sets the normalization details of the target columns. By default these values will be null. If the target column is normalized, then the test metrics computed will have measures based on normalized target values. To provide denormalized test metrics use this method to set the target normalization details. operation will be normalized.

Parameters:

shiftValue -

scaleValue -

getTargetNormalizationShiftValue

public java.lang.Double getTargetNormalizationShiftValue()

Returns the specified normalization shift value of the target column. It returns null value if it is not specified.

Returns:

getTargetNormalizationScaleValue

public java.lang.Double getTargetNormalizationScaleValue()

Returns the specified normalization scale value of the target column. It returns null value if it is not specified.

Returns: