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Oracle Data Mining Java API Reference
11g Release 2 (11.2)

E12219-03


oracle.dmt.jdm.algorithm.svm.regression
Class OraSVMRegressionSettings

java.lang.Object
  extended byoracle.dmt.jdm.OraDMObject
      extended byoracle.dmt.jdm.base.OraAlgorithmSettings
          extended byoracle.dmt.jdm.supervised.OraSupervisedAlgorithmSettings
              extended byoracle.dmt.jdm.algorithm.svm.regression.OraSVMRegressionSettings

All Implemented Interfaces:
javax.datamining.base.AlgorithmSettings, oracle.dmt.jdm.OraPLSQLConstants, javax.datamining.supervised.SupervisedAlgorithmSettings, javax.datamining.algorithm.svm.regression.SVMRegressionSettings

public class OraSVMRegressionSettings
extends oracle.dmt.jdm.supervised.OraSupervisedAlgorithmSettings
implements javax.datamining.algorithm.svm.regression.SVMRegressionSettings

OraSVMRegressionSettings defines oracle specific SVM algorithm settings i.e., active learning.


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
 boolean getActiveLearning()
          Returns true if active learning by algorithm is enabled, either set by the user or the default value.
 void setActiveLearning(boolean enable)
          Sets to true to enable active learning by algorithm, otherwise sets to false.

 

Methods inherited from class oracle.dmt.jdm.base.OraAlgorithmSettings
getMiningAlgorithm, verify

 

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.AlgorithmSettings
getMiningAlgorithm, verify

 

Method Detail

getActiveLearning

public boolean getActiveLearning()
Returns true if active learning by algorithm is enabled, either set by the user or the default value. Active learning is enabled by default.
Returns:
boolean
Throws:
javax.datamining.JDMException

setActiveLearning

public void setActiveLearning(boolean enable)
Sets to true to enable active learning by algorithm, otherwise sets to false.
Parameters:
enable - True if active learning is enabled.
Returns:
void
Throws:
javax.datamining.JDMException

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Oracle Data Mining Java API Reference
11g Release 2 (11.2)

E12219-03


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