A program to recognize and reward our most engaged community members
<?xml version="1.0" encoding="UTF-8" standalone="no"?><process version="5.0"> <context> <input/> <output/> <macros/> </context> <operator activated="true" class="process" compatibility="5.1.8" expanded="true" name="Process"> <parameter key="logfile" value="/home/yzheng/workspace/alldata/svm-log-sys.csv"/> <parameter key="resultfile" value="/home/yzheng/workspace/alldata/svmgrid-result.csv"/> <process expanded="true" height="360" width="1005"> <operator activated="true" class="read_csv" compatibility="5.0.10" expanded="true" height="60" name="Read CSV" width="90" x="45" y="30"> <parameter key="file_name" value="/home/yzheng/workspace/alldata/svmgrid-data-new.csv"/> <parameter key="encoding" value="UTF-8"/> <parameter key="trim_lines" value="true"/> <parameter key="column_separators" value=","/> <parameter key="read_not_matching_values_as_missings" value="false"/> <list key="data_set_meta_data_information"/> </operator> <operator activated="true" class="guess_types" compatibility="5.0.10" expanded="true" height="76" name="Guess Types" width="90" x="177" y="84"> <parameter key="block_type" value="value_matrix"/> </operator> <operator activated="true" class="set_role" compatibility="5.0.10" expanded="true" height="76" name="Set Role (3)" width="90" x="313" y="120"> <parameter key="name" value="class"/> <parameter key="target_role" value="label"/> </operator> <operator activated="true" class="optimize_parameters_grid" compatibility="5.1.8" expanded="true" height="112" name="Optimize Parameters (Grid)" width="90" x="514" y="75"> <list key="parameters"> <parameter key="SVM.C" value="[1;10;100;linear]"/> </list> <process expanded="true" height="360" width="1005"> <operator activated="true" class="x_validation" compatibility="5.1.8" expanded="true" height="112" name="Validation" width="90" x="324" y="133"> <parameter key="average_performances_only" value="false"/> <parameter key="local_random_seed" value="1978"/> <process expanded="true" height="360" width="477"> <operator activated="true" class="support_vector_machine_libsvm" compatibility="5.0.10" expanded="true" height="76" name="SVM" width="90" x="190" y="86"> <parameter key="kernel_type" value="linear"/> <parameter key="C" value="10.0"/> <list key="class_weights"/> </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="36"/> <portSpacing port="sink_model" spacing="0"/> <portSpacing port="sink_through 1" spacing="0"/> </process> <process expanded="true" height="360" width="477"> <operator activated="true" class="apply_model" compatibility="5.1.8" 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="5.0.10" expanded="true" height="76" name="Performance" width="90" x="246" y="30"> <parameter key="main_criterion" value="accuracy"/> <parameter key="weighted_mean_recall" value="true"/> <parameter key="weighted_mean_precision" 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="5.1.8" expanded="true" height="76" name="Log" width="90" x="514" y="120"> <parameter key="filename" value="/home/yzheng/workspace/alldata/svmgrid-log-performance.csv"/> <list key="log"> <parameter key="c" value="operator.SVM.parameter.C"/> <parameter key="accuracy" value="operator.Performance.value.accuracy"/> <parameter key="precision" value="operator.Performance.value.weighted_mean_precision"/> <parameter key="recall" value="operator.Performance.value.weighted_mean_recall"/> </list> </operator> <connect from_port="input 1" to_op="Validation" to_port="training"/> <connect from_op="Validation" from_port="averagable 1" to_op="Log" to_port="through 1"/> <connect from_op="Log" from_port="through 1" to_port="performance"/> <portSpacing port="source_input 1" spacing="90"/> <portSpacing port="source_input 2" spacing="18"/> <portSpacing port="sink_performance" spacing="0"/> <portSpacing port="sink_result 1" spacing="0"/> <portSpacing port="sink_result 2" spacing="0"/> </process> </operator> <operator activated="true" class="write" compatibility="5.0.10" expanded="true" height="60" name="Write" width="90" x="715" y="165"> <parameter key="object_file" value="/home/yzheng/workspace/alldata/svmgrid-result"/> <parameter key="output_type" value="XML"/> </operator> <connect from_op="Read CSV" from_port="output" to_op="Guess Types" to_port="example set input"/> <connect from_op="Guess Types" from_port="example set output" to_op="Set Role (3)" to_port="example set input"/> <connect from_op="Set Role (3)" from_port="example set output" to_op="Optimize Parameters (Grid)" to_port="input 1"/> <connect from_op="Optimize Parameters (Grid)" from_port="parameter" to_op="Write" to_port="object"/> <connect from_op="Optimize Parameters (Grid)" from_port="result 1" to_port="result 2"/> <connect from_op="Write" from_port="object" to_port="result 1"/> <portSpacing port="source_input 1" spacing="36"/> <portSpacing port="sink_result 1" spacing="0"/> <portSpacing port="sink_result 2" spacing="0"/> <portSpacing port="sink_result 3" spacing="0"/> </process> </operator></process>