"Text Classification with different terms"

User: "dport"
New Altair Community Member
Updated by Jocelyn
I would like to classify an example set based on a classification model generated from a related but different example set. The terms will not be identical. Is it reasonable to supply the word list form the model to the example set I wish to classify?

The model I am experimenting with is listed below. It seems to give pretty decent results but I have yet to give it full check (this would require a lot of data preparation).

Any feedback appreciated!

<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="5.0">
 <context>
   <input>
     <location/>
   </input>
   <output>
     <location/>
     <location/>
   </output>
   <macros/>
 </context>
 <operator activated="true" class="process" expanded="true" name="Process">
   <process expanded="true" height="448" width="748">
     <operator activated="true" class="retrieve" expanded="true" height="60" name="Retrieve" width="90" x="45" y="75">
       <parameter key="repository_entry" value="team_x_risks_no_dups"/>
     </operator>
     <operator activated="true" class="nominal_to_text" expanded="true" height="76" name="Nominal to Text" width="90" x="179" y="75">
       <parameter key="attribute_filter_type" value="subset"/>
       <parameter key="attribute" value="risk_title risk_desc_risk_keywords_risk_factor_description"/>
       <parameter key="attributes" value="risk_all"/>
     </operator>
     <operator activated="true" class="retrieve" expanded="true" height="60" name="Retrieve (2)" width="90" x="45" y="300">
       <parameter key="repository_entry" value="team_x_risk_cats"/>
     </operator>
     <operator activated="true" class="nominal_to_text" expanded="true" height="76" name="Nominal to Text (2)" width="90" x="179" y="300"/>
     <operator activated="true" class="text:process_document_from_data" expanded="true" height="76" name="Process Documents from Data" width="90" x="313" y="300">
       <list key="specify_weights"/>
       <process expanded="true">
         <operator activated="true" class="text:tokenize" expanded="true" height="60" name="Tokenize" width="90" x="45" y="75"/>
         <operator activated="true" class="text:transform_cases" expanded="true" height="60" name="Transform Cases (2)" width="90" x="179" y="210"/>
         <operator activated="true" class="text:filter_stopwords_english" expanded="true" height="60" name="Filter Stopwords (2)" width="90" x="313" y="300"/>
         <operator activated="true" class="text:filter_by_length" expanded="true" height="60" name="Filter Tokens (2)" width="90" x="458" y="288">
           <parameter key="min_chars" value="3"/>
         </operator>
         <operator activated="true" class="text:generate_n_grams_terms" expanded="true" height="60" name="Generate n-Grams (2)" width="90" x="715" y="120"/>
         <connect from_port="document" to_op="Tokenize" to_port="document"/>
         <connect from_op="Tokenize" from_port="document" to_op="Transform Cases (2)" to_port="document"/>
         <connect from_op="Transform Cases (2)" from_port="document" to_op="Filter Stopwords (2)" to_port="document"/>
         <connect from_op="Filter Stopwords (2)" from_port="document" to_op="Filter Tokens (2)" to_port="document"/>
         <connect from_op="Filter Tokens (2)" from_port="document" to_op="Generate n-Grams (2)" to_port="document"/>
         <connect from_op="Generate n-Grams (2)" 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="k_nn" expanded="true" height="76" name="k-NN" width="90" x="447" y="300">
       <parameter key="measure_types" value="NumericalMeasures"/>
       <parameter key="numerical_measure" value="CosineSimilarity"/>
     </operator>
     <operator activated="true" class="text:process_document_from_data" expanded="true" height="76" name="Process Documents from Data (2)" width="90" x="313" y="75">
       <parameter key="keep_text" value="true"/>
       <parameter key="prune_method" value="percentual"/>
       <parameter key="prune_above_percent" value="50.0"/>
       <list key="specify_weights"/>
       <process expanded="true">
         <operator activated="true" class="text:tokenize" expanded="true" height="60" name="Tokenize (2)" width="90" x="45" y="30"/>
         <operator activated="true" class="text:transform_cases" expanded="true" height="60" name="Transform Cases" width="90" x="179" y="75"/>
         <operator activated="true" class="text:filter_stopwords_english" expanded="true" height="60" name="Filter Stopwords (English)" width="90" x="313" y="210"/>
         <operator activated="true" class="text:filter_by_length" expanded="true" height="60" name="Filter Tokens (by Length)" width="90" x="447" y="120">
           <parameter key="min_chars" value="3"/>
         </operator>
         <operator activated="true" class="text:generate_n_grams_terms" expanded="true" height="60" name="Generate n-Grams (Terms)" width="90" x="514" y="30"/>
         <connect from_port="document" to_op="Tokenize (2)" to_port="document"/>
         <connect from_op="Tokenize (2)" from_port="document" to_op="Transform Cases" to_port="document"/>
         <connect from_op="Transform Cases" from_port="document" to_op="Filter Stopwords (English)" to_port="document"/>
         <connect from_op="Filter Stopwords (English)" from_port="document" to_op="Filter Tokens (by Length)" to_port="document"/>
         <connect from_op="Filter Tokens (by Length)" from_port="document" to_op="Generate n-Grams (Terms)" to_port="document"/>
         <connect from_op="Generate n-Grams (Terms)" 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="apply_model" expanded="true" height="76" name="Apply Model" width="90" x="581" y="165">
       <list key="application_parameters"/>
     </operator>
     <connect from_op="Retrieve" from_port="output" to_op="Nominal to Text" to_port="example set input"/>
     <connect from_op="Nominal to Text" from_port="example set output" to_op="Process Documents from Data (2)" to_port="example set"/>
     <connect from_op="Retrieve (2)" from_port="output" to_op="Nominal to Text (2)" to_port="example set input"/>
     <connect from_op="Nominal to Text (2)" from_port="example set output" to_op="Process Documents from Data" to_port="example set"/>
     <connect from_op="Process Documents from Data" from_port="example set" to_op="k-NN" to_port="training set"/>
     <connect from_op="Process Documents from Data" from_port="word list" to_op="Process Documents from Data (2)" to_port="word list"/>
     <connect from_op="k-NN" from_port="model" to_op="Apply Model" to_port="model"/>
     <connect from_op="Process Documents from Data (2)" from_port="example set" to_op="Apply Model" to_port="unlabelled data"/>
     <connect from_op="Apply Model" from_port="labelled data" 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>

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