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"SVM and Bootstrapping"
holdwater587
Member Posts: 5 
Contributor II
Hi, i am a newbie
i have a data of 5 attributes and 200 rows and use epsilon-SVR.
First, i want to get 100 bootstrap sample and then use each sample on my SVM model.
Each SVM model will predict my test data.
And finally i want to plot these 100 predictions on the same graph.
Shortly, it is like i have 100 training data and so 100 different SVM model and i want to test all these on my test data.
Is it possible in rapidminer (can we use loop etc.)
Thx in advance
i have a data of 5 attributes and 200 rows and use epsilon-SVR.
First, i want to get 100 bootstrap sample and then use each sample on my SVM model.
Each SVM model will predict my test data.
And finally i want to plot these 100 predictions on the same graph.
Shortly, it is like i have 100 training data and so 100 different SVM model and i want to test all these on my test data.
Is it possible in rapidminer (can we use loop etc.)
Thx in advance
Tagged:
0
Answers
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="5.1.008">
<context>
<input/>
<output/>
<macros/>
</context>
<operator activated="true" class="process" compatibility="5.1.008" expanded="true" name="Process">
<process expanded="true" height="377" width="547">
<operator activated="true" class="retrieve" compatibility="5.1.008" expanded="true" height="60" name="Retrieve" width="90" x="45" y="30">
<parameter key="repository_entry" value="//Samples/data/Sonar"/>
</operator>
<operator activated="true" class="nominal_to_numerical" compatibility="5.1.008" expanded="true" height="94" name="Nominal to Numerical" width="90" x="179" y="30">
<parameter key="attribute_filter_type" value="single"/>
<parameter key="attribute" value="class"/>
<parameter key="include_special_attributes" value="true"/>
</operator>
<operator activated="true" class="bootstrapping_validation" compatibility="5.1.008" expanded="true" height="112" name="Validation" width="90" x="313" y="30">
<process expanded="true" height="409" width="165">
<operator activated="true" class="support_vector_machine_libsvm" compatibility="5.1.008" expanded="true" height="76" name="SVM" width="90" x="45" y="30">
<parameter key="svm_type" value="epsilon-SVR"/>
<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="0"/>
<portSpacing port="sink_model" spacing="0"/>
<portSpacing port="sink_through 1" spacing="0"/>
</process>
<process expanded="true" height="409" width="300">
<operator activated="true" class="apply_model" compatibility="5.1.008" expanded="true" height="76" name="Apply Model" width="90" x="45" y="30">
<list key="application_parameters"/>
</operator>
<operator activated="true" class="performance" compatibility="5.1.008" expanded="true" height="76" name="Performance (2)" width="90" x="179" y="30"/>
<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 (2)" to_port="labelled data"/>
<connect from_op="Performance (2)" 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>
<connect from_op="Retrieve" from_port="output" to_op="Nominal to Numerical" to_port="example set input"/>
<connect from_op="Nominal to Numerical" from_port="example set output" to_op="Validation" to_port="training"/>
<connect from_op="Validation" from_port="averagable 1" 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>
This writes out predictions to a file, and retrieves them later to plot.
Might be a better way to do this.
If so, please let me know.
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="5.1.008">
<context>
<input/>
<output/>
<macros/>
</context>
<operator activated="true" class="process" compatibility="5.1.008" expanded="true" name="Process">
<process expanded="true" height="409" width="815">
<operator activated="true" class="retrieve" compatibility="5.1.008" expanded="true" height="60" name="Retrieve" width="90" x="45" y="30">
<parameter key="repository_entry" value="//Samples/data/Polynomial"/>
</operator>
<operator activated="true" class="bootstrapping_validation" compatibility="5.1.008" expanded="true" height="112" name="Validation" width="90" x="313" y="30">
<process expanded="true" height="409" width="165">
<operator activated="true" class="support_vector_machine_libsvm" compatibility="5.1.008" expanded="true" height="76" name="SVM" width="90" x="45" y="30">
<parameter key="svm_type" value="epsilon-SVR"/>
<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="0"/>
<portSpacing port="sink_model" spacing="0"/>
<portSpacing port="sink_through 1" spacing="0"/>
</process>
<process expanded="true" height="409" width="480">
<operator activated="true" class="apply_model" compatibility="5.1.008" expanded="true" height="76" name="Apply Model" width="90" x="45" y="30">
<list key="application_parameters"/>
</operator>
<operator activated="true" class="select_attributes" compatibility="5.1.008" expanded="true" height="76" name="Select Attributes" width="90" x="45" y="120">
<parameter key="attribute_filter_type" value="single"/>
<parameter key="attribute" value="prediction(label)"/>
<parameter key="include_special_attributes" value="true"/>
</operator>
<operator activated="true" class="transpose" compatibility="5.1.008" expanded="true" height="76" name="Transpose" width="90" x="45" y="255"/>
<operator activated="true" class="performance" compatibility="5.1.008" expanded="true" height="76" name="Performance (2)" width="90" x="313" y="30"/>
<operator activated="true" class="write_special" compatibility="5.1.008" expanded="true" height="60" name="Write Special Format" width="90" x="179" y="255">
<parameter key="example_set_file" value="C:\Users\wessel\Desktop\z"/>
<parameter key="special_format" value="$a"/>
</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="Select Attributes" to_port="example set input"/>
<connect from_op="Select Attributes" from_port="example set output" to_op="Transpose" to_port="example set input"/>
<connect from_op="Select Attributes" from_port="original" to_op="Performance (2)" to_port="labelled data"/>
<connect from_op="Transpose" from_port="example set output" to_op="Write Special Format" to_port="input"/>
<connect from_op="Performance (2)" 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="read_csv" compatibility="5.1.008" expanded="true" height="60" name="Read CSV" width="90" x="45" y="255">
<parameter key="csv_file" value="C:\Users\wessel\Desktop\z"/>
<parameter key="column_separators" value=" "/>
<parameter key="first_row_as_names" value="false"/>
<list key="annotations"/>
<list key="data_set_meta_data_information"/>
</operator>
<operator activated="true" class="transpose" compatibility="5.1.008" expanded="true" height="76" name="Transpose (2)" width="90" x="313" y="255"/>
<operator activated="true" class="generate_id" compatibility="5.1.008" expanded="true" height="76" name="Generate ID (2)" width="90" x="444" y="255"/>
<operator activated="true" class="generate_id" compatibility="5.1.008" expanded="true" height="76" name="Generate ID" width="90" x="447" y="165"/>
<operator activated="true" class="join" compatibility="5.1.008" expanded="true" height="76" name="Join" width="90" x="581" y="210"/>
<operator activated="true" class="rename_by_replacing" compatibility="5.1.008" expanded="true" height="76" name="Rename by Replacing" width="90" x="715" y="210">
<parameter key="replace_what" value="att"/>
<parameter key="replace_by" value="pred"/>
</operator>
<connect from_op="Retrieve" from_port="output" to_op="Validation" to_port="training"/>
<connect from_op="Validation" from_port="training" to_op="Generate ID" to_port="example set input"/>
<connect from_op="Validation" from_port="averagable 1" to_port="result 1"/>
<connect from_op="Read CSV" from_port="output" to_op="Transpose (2)" to_port="example set input"/>
<connect from_op="Transpose (2)" from_port="example set output" to_op="Generate ID (2)" to_port="example set input"/>
<connect from_op="Generate ID (2)" from_port="example set output" to_op="Join" to_port="right"/>
<connect from_op="Generate ID" from_port="example set output" to_op="Join" to_port="left"/>
<connect from_op="Join" from_port="join" to_op="Rename by Replacing" to_port="example set input"/>
<connect from_op="Rename by Replacing" from_port="example set output" to_port="result 2"/>
<portSpacing port="source_input 1" spacing="0"/>
<portSpacing port="sink_result 1" spacing="0"/>
<portSpacing port="sink_result 2" spacing="216"/>
<portSpacing port="sink_result 3" spacing="0"/>
</process>
</operator>
</process>