Support vector machine regression LibSVM and PSO

ismail_hdoufane

Dear Community,

 

I am a new user. I have an xls file which contains 159 rows and 13 columns. 

1st column contains values of biological activity (Y) and the others contain(molecular descriptors)  (Xi)

I would like to do Regression for building model using Support Vector Machine LibSVM and PSO.

Best Regards,

Ismail

Thomas_Ott

You will need a Read Excel, Set Role, Cross Validation, LibSVM, Apply Model and Performance operators as a starting point for your process. Something like this below:

 

<?xml version="1.0" encoding="UTF-8"?><process version="7.6.002">
  <context>
    <input/>
    <output/>
    <macros/>
  </context>
  <operator activated="true" class="process" compatibility="7.6.002" expanded="true" name="Process">
    <process expanded="true">
      <operator activated="true" class="read_excel" compatibility="7.6.002" expanded="true" height="68" name="Read Excel" width="90" x="112" y="34">
        <list key="annotations"/>
        <list key="data_set_meta_data_information"/>
      </operator>
      <operator activated="true" class="set_role" compatibility="7.6.002" expanded="true" height="82" name="Set Role" width="90" x="246" y="34">
        <list key="set_additional_roles"/>
      </operator>
      <operator activated="true" class="concurrency:cross_validation" compatibility="7.6.002" expanded="true" height="145" name="Validation" width="90" x="380" y="34">
        <parameter key="sampling_type" value="shuffled sampling"/>
        <process expanded="true">
          <operator activated="true" class="support_vector_machine_libsvm" compatibility="7.6.002" expanded="true" height="82" name="SVM" width="90" x="227" y="34">
            <parameter key="svm_type" value="epsilon-SVR"/>
            <list key="class_weights"/>
          </operator>
          <connect from_port="training set" to_op="SVM" to_port="training set"/>
          <connect from_op="SVM" from_port="model" to_port="model"/>
          <portSpacing port="source_training set" spacing="0"/>
          <portSpacing port="sink_model" spacing="0"/>
          <portSpacing port="sink_through 1" spacing="0"/>
        </process>
        <process expanded="true">
          <operator activated="true" class="apply_model" compatibility="7.6.002" expanded="true" height="82" name="Apply Model" width="90" x="45" y="34">
            <list key="application_parameters"/>
          </operator>
          <operator activated="true" class="performance" compatibility="7.6.002" expanded="true" height="82" name="Performance" width="90" x="179" y="34"/>
          <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="performance 1"/>
          <connect from_op="Performance" from_port="example set" to_port="test set results"/>
          <portSpacing port="source_model" spacing="0"/>
          <portSpacing port="source_test set" spacing="0"/>
          <portSpacing port="source_through 1" spacing="0"/>
          <portSpacing port="sink_test set results" spacing="0"/>
          <portSpacing port="sink_performance 1" spacing="0"/>
          <portSpacing port="sink_performance 2" spacing="0"/>
          <description align="left" color="blue" colored="true" height="107" resized="true" width="333" x="28" y="139">Applies the model built from the training data set on the current test set (10 % by default).&lt;br/&gt;The Performance operator calculates performance indicators and sends them to the operator result.</description>
        </process>
        <description align="center" color="transparent" colored="false" width="126">A cross validation including a linear regression.</description>
      </operator>
      <connect from_op="Read Excel" from_port="output" to_op="Set Role" to_port="example set input"/>
      <connect from_op="Set Role" from_port="example set output" to_op="Validation" to_port="example set"/>
      <connect from_op="Validation" from_port="model" to_port="result 1"/>
      <connect from_op="Validation" from_port="performance 1" to_port="result 2"/>
      <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"/>
    </process>
  </operator>
</process>

SGolbert

To expand a bit on the topic: what are the big differences between the SVM operator and the LibSVM one? When would you use one instead of the other?