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<operator name="Root" class="Process" expanded="yes"> <operator name="ExampleSetGenerator" class="ExampleSetGenerator"> <parameter key="target_function" value="two gaussians classification"/> <parameter key="number_of_attributes" value="10"/> </operator> <operator name="BruteForce" class="BruteForce" expanded="yes"> <operator name="NaiveBayes" class="NaiveBayes"> <parameter key="keep_example_set" value="true"/> </operator> <operator name="ModelApplier" class="ModelApplier"> <list key="application_parameters"> </list> </operator> <operator name="BinominalClassificationPerformance" class="BinominalClassificationPerformance"> <parameter key="main_criterion" value="youden"/> <parameter key="sensitivity" value="true"/> <parameter key="specificity" value="true"/> <parameter key="youden" value="true"/> </operator> <operator name="ProcessLog" class="ProcessLog"> <parameter key="filename" value="log.txt"/> <list key="log"> <parameter key="features" value="operator.BruteForce.value.feature_names"/> <parameter key="sensitivity" value="operator.BinominalClassificationPerformance.value.sensitivity"/> <parameter key="specificity" value="operator.BinominalClassificationPerformance.value.specificity"/> </list> </operator> </operator></operator>
<?xml version="1.0" encoding="UTF-8" standalone="no"?><process version="5.0"> <context> <input> <location/> </input> <output> <location/> <location/> </output> <macros/> </context> <operator activated="true" class="process" expanded="true" name="Process"> <process expanded="true" height="471" width="279"> <operator activated="true" class="generate_data" expanded="true" height="60" name="Generate Data" width="90" x="45" y="30"> <parameter key="target_function" value="two gaussians classification"/> <parameter key="number_of_attributes" value="10"/> </operator> <operator activated="true" class="optimize_selection_brute_force" expanded="true" height="94" name="Optimize Selection (Brute Force)" width="90" x="179" y="30"> <process expanded="true" height="489" width="679"> <operator activated="true" class="naive_bayes" expanded="true" height="76" name="Naive Bayes" width="90" x="45" y="30"/> <operator activated="true" class="apply_model" expanded="true" height="76" name="Apply Model" width="90" x="179" y="30"> <list key="application_parameters"/> </operator> <operator activated="true" class="performance_binominal_classification" expanded="true" height="76" name="Performance" width="90" x="313" y="30"> <parameter key="main_criterion" value="youden"/> <parameter key="sensitivity" value="true"/> <parameter key="specificity" value="true"/> <parameter key="youden" value="true"/> </operator> <operator activated="true" class="log" expanded="true" height="76" name="Log" width="90" x="447" y="30"> <parameter key="filename" value="log.txt"/> <list key="log"> <parameter key="features" value="operator.Optimize Selection (Brute Force).value.feature_names"/> <parameter key="sensitivity" value="operator.Performance.value.sensitivity"/> <parameter key="specificity" value="operator.Performance.value.specificity"/> </list> </operator> <connect from_port="example set" to_op="Naive Bayes" to_port="training set"/> <connect from_op="Naive Bayes" from_port="model" to_op="Apply Model" to_port="model"/> <connect from_op="Naive Bayes" from_port="exampleSet" to_op="Apply Model" to_port="unlabelled data"/> <connect from_op="Apply Model" from_port="labelled data" to_op="Performance" to_port="labelled data"/> <connect from_op="Performance" from_port="performance" to_op="Log" to_port="through 1"/> <connect from_op="Log" from_port="through 1" to_port="performance"/> <portSpacing port="source_example set" spacing="0"/> <portSpacing port="source_through 1" spacing="0"/> <portSpacing port="sink_performance" spacing="0"/> </process> </operator> <connect from_op="Generate Data" from_port="output" to_op="Optimize Selection (Brute Force)" to_port="example set in"/> <connect from_op="Optimize Selection (Brute Force)" from_port="example set out" to_port="result 1"/> <portSpacing port="source_input 1" spacing="0"/> <portSpacing port="sink_result 1" spacing="0"/> <portSpacing port="sink_result 2" spacing="0"/> </process> </operator></process>
<operator name="Root" class="Process" expanded="yes"> <operator name="ExampleSetGenerator" class="ExampleSetGenerator"> <parameter key="target_function" value="two gaussians classification"/> <parameter key="number_of_attributes" value="10"/> </operator> <operator name="BruteForce" class="BruteForce" expanded="yes"> <operator name="Reset" class="SingleMacroDefinition"> <parameter key="macro" value="All"/> <parameter key="value" value="Using-"/> </operator> <operator name="FeatureIterator" class="FeatureIterator" expanded="no"> <operator name="SingleMacroDefinition" class="SingleMacroDefinition"> <parameter key="macro" value="All"/> <parameter key="value" value="%{All},%{loop_feature}"/> </operator> </operator> <operator name="NaiveBayes" class="NaiveBayes"> <parameter key="keep_example_set" value="true"/> </operator> <operator name="ModelApplier" class="ModelApplier"> <list key="application_parameters"> </list> </operator> <operator name="BinominalClassificationPerformance" class="BinominalClassificationPerformance"> <parameter key="main_criterion" value="youden"/> <parameter key="sensitivity" value="true"/> <parameter key="specificity" value="true"/> <parameter key="youden" value="true"/> </operator> <operator name="Macro2Log" class="Macro2Log"> <parameter key="macro_name" value="All"/> </operator> <operator name="ProcessLog" class="ProcessLog"> <list key="log"> <parameter key="features" value="operator.Macro2Log.value.macro_value"/> <parameter key="sensitivity" value="operator.BinominalClassificationPerformance.value.sensitivity"/> <parameter key="specificity" value="operator.BinominalClassificationPerformance.value.performance"/> </list> </operator> </operator></operator>