Hi All
when i using Rapidminer for optimization a problems, its run for some time faster and then slowly and finally stopped without complete all generation that i wanted. therefor the problem didn't optimized, and the performance very bad.
any help???
my PC specification
RAM:32G
CPU: i7-3820
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="5.2.006">
<context>
<input/>
<output/>
<macros/>
</context>
<operator activated="true" class="process" compatibility="5.2.006" expanded="true" name="Process">
<process expanded="true" height="650" width="748">
<operator activated="true" class="retrieve" compatibility="5.2.006" expanded="true" height="60" name="Retrieve" width="90" x="13" y="106">
<parameter key="repository_entry" value="../Gene Expression DataSet/LungCancer"/>
</operator>
<operator activated="true" class="normalize" compatibility="5.2.006" expanded="true" height="94" name="Normalize" width="90" x="246" y="120">
<parameter key="method" value="range transformation"/>
</operator>
<operator activated="true" class="parallel:optimize_selection_evolutionary_parallel" compatibility="5.1.000" expanded="true" height="94" name="Optimize Selection (Evolutionary)" width="90" x="581" y="165">
<parameter key="restrict_maximum" value="true"/>
<parameter key="min_number_of_attributes" value="2"/>
<parameter key="max_number_of_attributes" value="10"/>
<parameter key="population_size" value="30"/>
<parameter key="maximum_number_of_generations" value="10"/>
<parameter key="generations_without_improval" value="5"/>
<parameter key="keep_best_individual" value="true"/>
<parameter key="p_mutation" value="0.1"/>
<parameter key="number_of_threads" value="3"/>
<parameter key="parallelize_evaluation_process" value="true"/>
<process expanded="true" height="632" width="570">
<operator activated="true" class="extract_macro" compatibility="5.2.006" expanded="true" height="60" name="Extract Macro" width="90" x="45" y="30">
<parameter key="macro" value="atts"/>
<parameter key="macro_type" value="number_of_attributes"/>
</operator>
<operator activated="true" class="loop_attribute_subsets" compatibility="5.2.006" expanded="true" height="60" name="Loop Subsets" width="90" x="180" y="30">
<parameter key="use_exact_number" value="true"/>
<parameter key="exact_number_of_attributes" value="%{atts}"/>
<process expanded="true">
<portSpacing port="source_example set" spacing="0"/>
</process>
</operator>
<operator activated="true" class="parallel:optimize_parameters_evolutionary_parallel" compatibility="5.1.000" expanded="true" height="112" name="Optimize Parameters (Evolutionary)" width="90" x="313" y="30">
<list key="parameters">
<parameter key="SVM.degree" value="[1.0;1000.0]"/>
<parameter key="SVM.gamma" value="[0.001;50.0]"/>
<parameter key="SVM.coef0" value="[0;100]"/>
<parameter key="SVM.C" value="[0.01;1000.0]"/>
</list>
<parameter key="generations_without_improval" value="5"/>
<parameter key="population_size" value="120"/>
<parameter key="mutation_type" value="switching_mutation"/>
<parameter key="number_of_threads" value="5"/>
<parameter key="parallelize_optimization_process" value="true"/>
<process expanded="true" height="650" width="300">
<operator activated="true" class="free_memory" compatibility="5.2.006" expanded="true" height="76" name="Free Memory" width="90" x="45" y="30"/>
<operator activated="true" class="optimize_parameters_grid" compatibility="5.2.006" expanded="true" height="94" name="Optimize Parameters (Grid)" width="90" x="180" y="30">
<list key="parameters">
<parameter key="SVM.kernel_type" value="linear,rbf,poly,sigmoid"/>
</list>
<parameter key="parallelize_optimization_process" value="true"/>
<process expanded="true" height="650" width="547">
<operator activated="true" class="x_validation" compatibility="5.2.006" expanded="true" height="112" name="Validation" width="90" x="313" y="75">
<parameter key="sampling_type" value="shuffled sampling"/>
<parameter key="use_local_random_seed" value="true"/>
<process expanded="true" height="650" width="304">
<operator activated="true" class="support_vector_machine_libsvm" compatibility="5.2.006" expanded="true" height="76" name="SVM" width="90" x="184" y="30">
<parameter key="kernel_type" value="poly"/>
<parameter key="degree" value="6"/>
<parameter key="gamma" value="37.72802935994529"/>
<parameter key="coef0" value="2.637011248736243"/>
<parameter key="C" value="119.2946119514599"/>
<list key="class_weights"/>
<parameter key="calculate_confidences" value="true"/>
</operator>
<connect from_port="training" to_op="SVM" to_port="training set"/>
<connect from_op="SVM" from_port="model" to_port="model"/>
<portSpacing port="source_training" spacing="0"/>
<portSpacing port="sink_model" spacing="0"/>
<portSpacing port="sink_through 1" spacing="0"/>
</process>
<process expanded="true" height="650" width="482">
<operator activated="true" class="apply_model" compatibility="5.2.006" expanded="true" height="76" name="Apply Model" width="90" x="45" y="30">
<list key="application_parameters"/>
</operator>
<operator activated="true" class="performance_classification" compatibility="5.2.006" expanded="true" height="76" name="Performance" width="90" x="179" y="30">
<parameter key="main_criterion" value="accuracy"/>
<parameter key="classification_error" value="true"/>
<list key="class_weights"/>
</operator>
<connect from_port="model" to_op="Apply Model" to_port="model"/>
<connect from_port="test set" 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_port="averagable 1"/>
<portSpacing port="source_model" spacing="0"/>
<portSpacing port="source_test set" spacing="0"/>
<portSpacing port="source_through 1" spacing="0"/>
<portSpacing port="sink_averagable 1" spacing="0"/>
<portSpacing port="sink_averagable 2" spacing="0"/>
</process>
</operator>
<operator activated="true" class="log" compatibility="5.2.006" expanded="true" height="76" name="Outer" width="90" x="447" y="75">
<list key="log">
<parameter key="SVM.C" value="operator.SVM.parameter.C"/>
<parameter key="SVM.GAMMA" value="operator.SVM.parameter.gamma"/>
<parameter key="SVM.DEGREE" value="operator.SVM.parameter.degree"/>
<parameter key="SVM.COEF" value="operator.SVM.parameter.coef0"/>
<parameter key="KERNEL.TYPE" value="operator.SVM.parameter.kernel_type"/>
<parameter key="PERFORMANCE" value="operator.Performance.value.performance"/>
<parameter key="LOOP.FATURESUBSET.NO" value="operator.Loop Subsets.value.feature_number"/>
<parameter key="LOOP.FEATURESUBSET.NAME" value="operator.Loop Subsets.value.feature_names"/>
<parameter key="Valid.perf" value="operator.Validation.value.performance"/>
</list>
</operator>
<connect from_port="input 1" to_op="Validation" to_port="training"/>
<connect from_op="Validation" from_port="averagable 1" to_op="Outer" to_port="through 1"/>
<connect from_op="Outer" from_port="through 1" to_port="performance"/>
<portSpacing port="source_input 1" spacing="0"/>
<portSpacing port="source_input 2" spacing="0"/>
<portSpacing port="sink_performance" spacing="0"/>
<portSpacing port="sink_result 1" spacing="0"/>
</process>
</operator>
<connect from_port="input 1" to_op="Free Memory" to_port="through 1"/>
<connect from_op="Free Memory" from_port="through 1" to_op="Optimize Parameters (Grid)" to_port="input 1"/>
<connect from_op="Optimize Parameters (Grid)" from_port="performance" to_port="performance"/>
<connect from_op="Optimize Parameters (Grid)" from_port="parameter" to_port="result 1"/>
<portSpacing port="source_input 1" spacing="0"/>
<portSpacing port="source_input 2" spacing="0"/>
<portSpacing port="sink_performance" spacing="0"/>
<portSpacing port="sink_result 1" spacing="0"/>
<portSpacing port="sink_result 2" spacing="0"/>
</process>
</operator>
<connect from_port="example set" to_op="Extract Macro" to_port="example set"/>
<connect from_op="Extract Macro" from_port="example set" to_op="Loop Subsets" to_port="example set"/>
<connect from_op="Loop Subsets" from_port="example set" to_op="Optimize Parameters (Evolutionary)" to_port="input 1"/>
<connect from_op="Optimize Parameters (Evolutionary)" from_port="performance" 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="Retrieve" from_port="output" to_op="Normalize" to_port="example set input"/>
<connect from_op="Normalize" from_port="example set output" to_op="Optimize Selection (Evolutionary)" to_port="example set in"/>
<connect from_op="Optimize Selection (Evolutionary)" from_port="example set out" to_port="result 1"/>
<connect from_op="Optimize Selection (Evolutionary)" from_port="weights" to_port="result 2"/>
<connect from_op="Optimize Selection (Evolutionary)" from_port="performance" to_port="result 3"/>
<portSpacing port="source_input 1" spacing="0"/>
<portSpacing port="sink_result 1" spacing="0"/>
<portSpacing port="sink_result 2" spacing="0"/>
<portSpacing port="sink_result 3" spacing="0"/>
<portSpacing port="sink_result 4" spacing="0"/>
</process>
</operator>
</process>
