"No accuracy matrix in SVM"

an0xan0x Member Posts: 3 Contributor I
edited June 12 in Help
Hi. I have a question about SVM in rapid miner. I dont know why svm couldn't create accuracy matrix as k-nn. it just shows root mean square error. what should I do?
I'm working on Text categorization and I have 3 columns. Title,Body and label. Body and title are text and label is numeric.
I used:
read database->process document->select attribute->set role(set label column as label)-> x-validation

<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="5.2.000">
<context>
  <input/>
  <output/>
  <macros/>
</context>
<operator activated="true" class="process" compatibility="5.2.000"
expanded="true" name="Process">
  <parameter key="parallelize_main_process" value="true"/>
  <process expanded="true" height="701" width="685">
    <operator activated="true" class="read_database"
compatibility="5.2.000" expanded="true" height="60" name="Read
Database" width="90" x="45" y="30">
      <parameter key="connection" value="ISNA_11News_Normalized"/>
      <parameter key="query" value="SELECT &quot;Title&quot;,
&quot;Body&quot;, &quot;Label&quot;&#10;FROM
&quot;dbo&quot;.&quot;nws_full_corpus&quot;"/>
      <parameter key="prepare_statement" value="true"/>
      <enumeration key="parameters"/>
    </operator>
    <operator activated="true"
class="text:process_document_from_data" compatibility="5.1.004"
expanded="true" height="76" name="Process Documents from Data"
width="90" x="179" y="30">
      <parameter key="prune_method" value="absolute"/>
      <parameter key="prune_below_absolute" value="2"/>
      <parameter key="prune_above_absolute" value="9999"/>
      <list key="specify_weights"/>
      <process expanded="true" height="298" width="671">
        <operator activated="true" class="text:transform_cases"
compatibility="5.1.004" expanded="true" height="60" name="Transform
Cases" width="90" x="45" y="30"/>
        <operator activated="true" class="text:tokenize"
compatibility="5.1.004" expanded="true" height="60" name="Tokenize"
width="90" x="45" y="165"/>
        <operator activated="true" class="text:filter_by_length"
compatibility="5.1.004" expanded="true" height="60" name="Filter
Tokens (by Length)" width="90" x="179" y="120">
          <parameter key="min_chars" value="2"/>
          <parameter key="max_chars" value="99999"/>
        </operator>
        <connect from_port="document" to_op="Transform Cases"
to_port="document"/>
        <connect from_op="Transform Cases" from_port="document"
to_op="Tokenize" to_port="document"/>
        <connect from_op="Tokenize" from_port="document"
to_op="Filter Tokens (by Length)" to_port="document"/>
        <connect from_op="Filter Tokens (by Length)"
from_port="document" to_port="document 1"/>
        <portSpacing port="source_document" spacing="0"/>
        <portSpacing port="sink_document 1" spacing="0"/>
        <portSpacing port="sink_document 2" spacing="0"/>
      </process>
    </operator>
    <operator activated="true" class="select_attributes"
compatibility="5.2.000" expanded="true" height="76" name="Select
Attributes" width="90" x="313" y="30">
      <parameter key="attribute_filter_type" value="no_missing_values"/>
      <parameter key="attribute" value="Label"/>
    </operator>
    <operator activated="true" class="set_role"
compatibility="5.2.000" expanded="true" height="76" name="Set Role"
width="90" x="447" y="30">
      <parameter key="name" value="Label"/>
      <parameter key="target_role" value="label"/>
      <list key="set_additional_roles"/>
    </operator>
    <operator activated="true" class="x_validation"
compatibility="5.2.000" expanded="true" height="112" name="Validation"
width="90" x="514" y="165">
      <parameter key="number_of_validations" value="2"/>
      <parameter key="sampling_type" value="shuffled sampling"/>
      <process expanded="true" height="332" width="346">
        <operator activated="true" class="support_vector_machine"
compatibility="5.2.000" expanded="true" height="112" name="SVM (3)"
width="90" x="179" y="120"/>
        <connect from_port="training" to_op="SVM (3)" to_port="training set"/>
        <connect from_op="SVM (3)" from_port="model" to_port="model"/>
        <connect from_op="SVM (3)" from_port="estimated performance"
to_port="through 1"/>
        <portSpacing port="source_training" spacing="0"/>
        <portSpacing port="sink_model" spacing="0"/>
        <portSpacing port="sink_through 1" spacing="0"/>
        <portSpacing port="sink_through 2" spacing="0"/>
      </process>
      <process expanded="true" height="298" width="310">
        <operator activated="true" class="apply_model"
compatibility="5.2.000" expanded="true" height="76" name="Apply Model"
width="90" x="45" y="30">
          <list key="application_parameters"/>
        </operator>
        <operator activated="true" class="performance"
compatibility="5.2.000" expanded="true" height="76" name="Performance"
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" 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="source_through 2" spacing="0"/>
        <portSpacing port="sink_averagable 1" spacing="0"/>
        <portSpacing port="sink_averagable 2" spacing="0"/>
      </process>
    </operator>
    <connect from_op="Read Database" from_port="output"
to_op="Process Documents from Data" to_port="example set"/>
    <connect from_op="Process Documents from Data"
from_port="example set" to_op="Select Attributes" to_port="example set
input"/>
    <connect from_op="Select Attributes" from_port="example set
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="training"/>
    <connect from_op="Validation" from_port="model" to_port="result 1"/>
    <connect from_op="Validation" from_port="training" to_port="result 2"/>
    <connect from_op="Validation" from_port="averagable 1"
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>
Tagged:

Answers

  • haddockhaddock Member Posts: 849  Guru
    Hi there,

    I see you are using the automatic performance chooser, and it seems not to please ! All is not lost however, you can pick exactly what you want using the 'Performance ( Classification )' operator. Hope that does the trick.

    Good weekend!
  • an0xan0x Member Posts: 3 Contributor I
    thank you for your solution.
    I want to try it, but performance (classification) doesn't work with integer label. RM offered use discretize, i did. but it says now label and prediction must be of the same , but are nominal and integer.

    <?xml version="1.0" encoding="UTF-8" standalone="no"?>
    <process version="5.2.000">
    <context>
    <input/>
    <output/>
    <macros/>
    </context>
    <operator activated="true" class="process" compatibility="5.2.000" expanded="true" name="Process">
    <parameter key="parallelize_main_process" value="true"/>
    <process expanded="true" height="701" width="685">
    <operator activated="true" class="read_database" compatibility="5.2.000" expanded="true" height="60" name="Read Database" width="90" x="45" y="30">
    <parameter key="connection" value="ISNA_11News_Normalized"/>
    <parameter key="query" value="SELECT &quot;Title&quot;, &quot;Body&quot;, &quot;Label&quot;&#10;FROM &quot;dbo&quot;.&quot;nws_full_corpus&quot;"/>
    <parameter key="prepare_statement" value="true"/>
    <enumeration key="parameters"/>
    </operator>
    <operator activated="true" class="text:process_document_from_data" compatibility="5.1.004" expanded="true" height="76" name="Process Documents from Data" width="90" x="179" y="30">
    <parameter key="prune_method" value="absolute"/>
    <parameter key="prune_below_absolute" value="2"/>
    <parameter key="prune_above_absolute" value="9999"/>
    <list key="specify_weights"/>
    <process expanded="true" height="298" width="671">
    <operator activated="true" class="text:transform_cases" compatibility="5.1.004" expanded="true" height="60" name="Transform Cases" width="90" x="45" y="30"/>
    <operator activated="true" class="text:tokenize" compatibility="5.1.004" expanded="true" height="60" name="Tokenize" width="90" x="45" y="165"/>
    <operator activated="true" class="text:filter_by_length" compatibility="5.1.004" expanded="true" height="60" name="Filter Tokens (by Length)" width="90" x="179" y="120">
    <parameter key="min_chars" value="2"/>
    <parameter key="max_chars" value="99999"/>
    </operator>
    <connect from_port="document" to_op="Transform Cases" to_port="document"/>
    <connect from_op="Transform Cases" from_port="document" to_op="Tokenize" to_port="document"/>
    <connect from_op="Tokenize" from_port="document" to_op="Filter Tokens (by Length)" to_port="document"/>
    <connect from_op="Filter Tokens (by Length)" from_port="document" to_port="document 1"/>
    <portSpacing port="source_document" spacing="0"/>
    <portSpacing port="sink_document 1" spacing="0"/>
    <portSpacing port="sink_document 2" spacing="0"/>
    </process>
    </operator>
    <operator activated="true" class="select_attributes" compatibility="5.2.000" expanded="true" height="76" name="Select Attributes" width="90" x="313" y="30">
    <parameter key="attribute_filter_type" value="no_missing_values"/>
    <parameter key="attribute" value="Label"/>
    </operator>
    <operator activated="true" class="set_role" compatibility="5.2.000" expanded="true" height="76" name="Set Role" width="90" x="447" y="30">
    <parameter key="name" value="Label"/>
    <parameter key="target_role" value="label"/>
    <list key="set_additional_roles"/>
    </operator>
    <operator activated="true" class="x_validation" compatibility="5.2.000" expanded="true" height="112" name="Validation" width="90" x="514" y="165">
    <parameter key="number_of_validations" value="2"/>
    <parameter key="sampling_type" value="shuffled sampling"/>
    <process expanded="true" height="332" width="346">
    <operator activated="true" class="support_vector_machine" compatibility="5.2.000" expanded="true" height="112" name="SVM (3)" width="90" x="179" y="120"/>
    <connect from_port="training" to_op="SVM (3)" to_port="training set"/>
    <connect from_op="SVM (3)" from_port="model" to_port="model"/>
    <connect from_op="SVM (3)" from_port="estimated performance" to_port="through 1"/>
    <portSpacing port="source_training" spacing="0"/>
    <portSpacing port="sink_model" spacing="0"/>
    <portSpacing port="sink_through 1" spacing="0"/>
    <portSpacing port="sink_through 2" spacing="0"/>
    </process>
    <process expanded="true" height="314" width="310">
    <operator activated="true" class="apply_model" compatibility="5.2.000" expanded="true" height="76" name="Apply Model" width="90" x="45" y="30">
    <list key="application_parameters"/>
    </operator>
    <operator activated="false" class="performance" compatibility="5.2.000" expanded="true" height="76" name="Performance" width="90" x="179" y="210"/>
    <operator activated="true" class="discretize_by_user_specification" compatibility="5.2.000" expanded="true" height="94" name="Discretize" width="90" x="45" y="165">
    <parameter key="attribute_filter_type" value="regular_expression"/>
    <parameter key="regular_expression" value="Label"/>
    <parameter key="include_special_attributes" value="true"/>
    <list key="classes">
    <parameter key="first" value="-Infinity"/>
    <parameter key="last" value="Infinity"/>
    </list>
    </operator>
    <operator activated="true" class="performance_classification" compatibility="5.2.000" expanded="true" height="76" name="Performance (2)" 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="Discretize" to_port="example set input"/>
    <connect from_op="Discretize" from_port="example set output" 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="source_through 2" spacing="0"/>
    <portSpacing port="sink_averagable 1" spacing="0"/>
    <portSpacing port="sink_averagable 2" spacing="0"/>
    </process>
    </operator>
    <connect from_op="Read Database" from_port="output" to_op="Process Documents from Data" to_port="example set"/>
    <connect from_op="Process Documents from Data" from_port="example set" to_op="Select Attributes" to_port="example set input"/>
    <connect from_op="Select Attributes" from_port="example set 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="training"/>
    <connect from_op="Validation" from_port="model" to_port="result 1"/>
    <connect from_op="Validation" from_port="training" to_port="result 2"/>
    <connect from_op="Validation" from_port="averagable 1" 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>
  • haddockhaddock Member Posts: 849  Guru
    Hi there,

    If you are doing classification you should convert the Label attribute type to nominal. If you work your way through 'help->Rapidminer tutorial' you'll see why the discretize operator is inappropriate.

    Good luck.
  • an0xan0x Member Posts: 3 Contributor I
    I had a problem with nominal labels. I use SVM and SVM doesn't work with nominal labels! If I convert it to nominal, SVM doesn't work. if keep it numerical, performance doesn't work. It's a loop!
  • haddockhaddock Member Posts: 849  Guru
    Hi there,

    Try using Bayes, or another learner that takes nominal attributes, like this
    <?xml version="1.0" encoding="UTF-8" standalone="no"?>
    <process version="5.2.000">
      <context>
        <input/>
        <output/>
        <macros/>
      </context>
      <operator activated="true" class="process" compatibility="5.2.000" expanded="true" name="Process">
        <parameter key="parallelize_main_process" value="true"/>
        <process expanded="true" height="701" width="685">
          <operator activated="true" class="generate_data" compatibility="5.2.000" expanded="true" height="60" name="Generate Data" width="90" x="179" y="165">
            <parameter key="target_function" value="simple non linear classification"/>
          </operator>
          <operator activated="true" class="discretize_by_user_specification" compatibility="5.2.000" expanded="true" height="94" name="Discretize" width="90" x="313" y="255">
            <parameter key="regular_expression" value="Label"/>
            <list key="classes">
              <parameter key="first" value="-Infinity"/>
              <parameter key="last" value="Infinity"/>
            </list>
          </operator>
          <operator activated="true" class="x_validation" compatibility="5.2.000" expanded="true" height="112" name="Validation" width="90" x="447" y="165">
            <parameter key="number_of_validations" value="2"/>
            <parameter key="sampling_type" value="shuffled sampling"/>
            <process expanded="true" height="332" width="346">
              <operator activated="false" class="support_vector_machine" compatibility="5.2.000" expanded="true" height="112" name="SVM (3)" width="90" x="179" y="30"/>
              <operator activated="true" class="naive_bayes" compatibility="5.2.000" expanded="true" height="76" name="Naive Bayes" width="90" x="179" y="165"/>
              <connect from_port="training" to_op="Naive Bayes" to_port="training set"/>
              <connect from_op="Naive Bayes" 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="314" width="310">
              <operator activated="true" class="apply_model" compatibility="5.2.000" expanded="true" height="76" name="Apply Model" width="90" x="45" y="30">
                <list key="application_parameters"/>
              </operator>
              <operator activated="false" class="performance" compatibility="5.2.000" expanded="true" height="76" name="Performance" width="90" x="179" y="210"/>
              <operator activated="true" class="performance_classification" compatibility="5.2.000" expanded="true" height="76" name="Performance (2)" 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 (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="Generate Data" from_port="output" to_op="Discretize" to_port="example set input"/>
          <connect from_op="Discretize" from_port="example set output" to_op="Validation" to_port="training"/>
          <connect from_op="Validation" from_port="model" to_port="result 1"/>
          <connect from_op="Validation" from_port="training" to_port="result 2"/>
          <connect from_op="Validation" from_port="averagable 1" 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>
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