<operator name="SimpleValidation (2)" class="SimpleValidation" breakpoints="after" expanded="yes"> <parameter key="local_random_seed" value="10"/> <operator name="JMySVMLearner" class="JMySVMLearner"> <parameter key="keep_example_set" value="true"/> <parameter key="max_iterations" value="100"/> <parameter key="calculate_weights" value="true"/> <parameter key="return_optimization_performance" value="true"/> <parameter key="estimate_performance" value="true"/> <parameter key="balance_cost" value="true"/> </operator> <operator name="ApplierChain (3)" class="OperatorChain" expanded="yes"> <operator name="Applier (3)" class="ModelApplier"> <parameter key="keep_model" value="true"/> <list key="application_parameters"> </list> <parameter key="create_view" value="true"/> </operator> <operator name="BinominalClassificationPerformance (2)" class="BinominalClassificationPerformance"> <parameter key="keep_example_set" value="true"/> <parameter key="main_criterion" value="AUC"/> <parameter key="AUC" value="true"/> <parameter key="lift" value="true"/> <parameter key="false_positive" value="true"/> <parameter key="false_negative" value="true"/> <parameter key="true_positive" value="true"/> <parameter key="true_negative" value="true"/> </operator> </operator>
<operator name="MetaCost" class="MetaCost" expanded="yes"> <parameter key="keep_example_set" value="true"/> <parameter key="cost_matrix" value="[0.0 1.0;5.0 0.0]"/> <operator name="SimpleValidation (2)" class="SimpleValidation" breakpoints="after" expanded="yes"> <parameter key="local_random_seed" value="10"/> <operator name="JMySVMLearner" class="JMySVMLearner"> <parameter key="keep_example_set" value="true"/> <parameter key="max_iterations" value="100"/> <parameter key="calculate_weights" value="true"/> <parameter key="return_optimization_performance" value="true"/> <parameter key="estimate_performance" value="true"/> <parameter key="balance_cost" value="true"/> </operator> <operator name="ApplierChain (3)" class="OperatorChain" expanded="yes"> <operator name="Applier (3)" class="ModelApplier"> <parameter key="keep_model" value="true"/> <list key="application_parameters"> </list> <parameter key="create_view" value="true"/> </operator> <operator name="BinominalClassificationPerformance (2)" class="BinominalClassificationPerformance"> <parameter key="keep_example_set" value="true"/> <parameter key="main_criterion" value="AUC"/> <parameter key="AUC" value="true"/> <parameter key="lift" value="true"/> <parameter key="false_positive" value="true"/> <parameter key="false_negative" value="true"/> <parameter key="true_positive" value="true"/> <parameter key="true_negative" value="true"/> </operator> </operator> </operator> </operator>
put the SVM directly into the MetaCost operator and then put the MetaCost operator as learner inside the SVM
<operator name="confidence estimate" class="XValidation" breakpoints="after" expanded="yes"> <parameter key="keep_example_set" value="true"/> <parameter key="create_complete_model" value="true"/> <operator name="MetaCost (2)" class="MetaCost" expanded="yes"> <parameter key="keep_example_set" value="true"/> <parameter key="cost_matrix" value="[0.0 3.0;1.0 0.0]"/> <operator name="KernelNaiveBayes (5)" class="KernelNaiveBayes"> <parameter key="keep_example_set" value="true"/> <parameter key="estimation_mode" value="full"/> <parameter key="number_of_kernels" value="35"/> </operator> </operator> <operator name="OperatorChain (2)" class="OperatorChain" expanded="yes"> <operator name="ModelApplier (2)" class="ModelApplier"> <parameter key="keep_model" value="true"/> <list key="application_parameters"> </list> <parameter key="create_view" value="true"/> </operator> <operator name="Performance (2)" class="Performance"> <parameter key="keep_example_set" value="true"/> </operator> </operator>