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oracle.dmt.jdm.supervised
Class OraTestTask

java.lang.Object
oracle.dmt.jdm.OraDMObject
oracle.dmt.jdm.OraMiningObject
oracle.dmt.jdm.base.OraTask
oracle.dmt.jdm.supervised.OraTestTask

All Implemented Interfaces:

javax.datamining.MiningObject, oracle.dmt.jdm.OraPLSQLConstants, javax.datamining.base.Task, javax.datamining.supervised.TestTask

Direct Known Subclasses:

OraClassificationTestTask

public abstract class OraTestTask

extends OraTask

implements javax.datamining.supervised.TestTask

OraTestTask is an extension of the javax.datamining.supervised.TestTask. It provides extension methods to retrieve the test input data details, description for test metrics and enabling/disabling of scoring cost matrix that is added to the input model.

See Also:

MiningObject, oracle.dmt.jdm.MiningObjectImpl, Task, oracle.dmt.jdm.base.TaskImpl, TestTask

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_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

javax.datamining.data.PhysicalDataSet	getTestData() Retrieves the test input data information from the task.
java.lang.String	getTestMetricsDescription() returns the description for the ClassificationTestMetrics object to be created.
void	setTestMetricsDescription(java.lang.String description) Sets the description for the ClassificationTestMetrics object to be created.
boolean	useCost() This method returns the flag that indicates the usage of the cost metric instead of probability to find the top prediction.
void	useCost(boolean useCost) This method specifies the flag that indicates the usage of the cost metric instead of probability to find the top prediction.

Methods inherited from class oracle.dmt.jdm.base.OraTask

addDependency, dropDependency, getChildTaskNames, getParentTaskNames, overwriteOutput, overwriteOutput

Methods inherited from class oracle.dmt.jdm.OraMiningObject

doBeforeStore, getCreationDate, getCreatorInfo, 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.base.Task

getExecutionHandle

Methods inherited from interface javax.datamining.MiningObject

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

Method Detail

getTestData

public javax.datamining.data.PhysicalDataSet getTestData()
                                                  throws javax.datamining.JDMException

Retrieves the test input data information from the task. This method returns null if the task is not retrived from the DME

Returns:

PhysicalDataSet test input data

Throws:

javax.datamining.JDMException

useCost

public void useCost(boolean useCost)

This method specifies the flag that indicates the usage of the cost metric instead of probability to find the top prediction. This flag is used only for classification models. For other models this settings is ignored.
In case of ClassificationTestTask by setting this flag to true will enable model's cost matrix (if any) and uses cost metric to determine the top prediction. In this case by default is set to true.
In case of ClassificationTestMetricsTask this flag is used to specify whether the specified 'score criterion column' represents the cost or not. In this case by default is set to false.

Since:

11.1.0.7

useCost

public boolean useCost()

This method returns the flag that indicates the usage of the cost metric instead of probability to find the top prediction. This flag is used only for classification models. For other models this settings is ignored.
In case of ClassificationTestTask by setting this flag to true will enable model's cost matrix (if any) and uses cost metric to determine the top prediction. In this case by default is set to true.
In case of ClassificationTestMetricsTask this flag is used to specify whether the specified 'score criterion column' represents the cost or not. In this case by default is set to false.

Since:

11.1.0.7

getTestMetricsDescription

public java.lang.String getTestMetricsDescription()

returns the description for the ClassificationTestMetrics object to be created.

Specified by:

getTestMetricsDescription in interface javax.datamining.supervised.TestTask

Returns:

String

Since:

1.1

setTestMetricsDescription

public void setTestMetricsDescription(java.lang.String description)

Sets the description for the ClassificationTestMetrics object to be created.

Specified by:

setTestMetricsDescription in interface javax.datamining.supervised.TestTask

Parameters:

description -

Returns:

void

Since:

1.1

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