I have a set of documents stored in a single folder. I run an unsupervised clustering algorithm, like K-means to construct two groups. Here is the workflow I created. Is there an approach that can separate the original folder into two folders based on the clustering result? In other words, I want to put the files belonging to cluster 1 into one folder and put the files belonging to cluster 2 into another folder.
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="5.1.011">
<context>
<input/>
<output/>
<macros/>
</context>
<operator activated="true" class="process" compatibility="5.1.011" expanded="true" name="Process">
<parameter key="parallelize_main_process" value="true"/>
<process expanded="true" height="370" width="656">
<operator activated="true" class="text:process_document_from_file" compatibility="5.1.002" expanded="true" height="76" name="Process Documents from Files (2)" width="90" x="45" y="75">
<list key="text_directories">
<parameter key="NotResponsive" value="D:\User1\datamining\Data\training Sets"/>
</list>
<parameter key="extract_text_only" value="false"/>
<parameter key="vector_creation" value="Term Frequency"/>
<parameter key="prune_method" value="absolute"/>
<parameter key="prune_below_absolute" value="5"/>
<parameter key="prune_above_absolute" value="5000000"/>
<parameter key="parallelize_vector_creation" value="true"/>
<process expanded="true" height="380" width="674">
<operator activated="true" class="text:tokenize" compatibility="5.1.002" expanded="true" height="60" name="Tokenize (2)" width="90" x="45" y="30"/>
<operator activated="true" class="text:transform_cases" compatibility="5.1.002" expanded="true" height="60" name="Transform Cases (2)" width="90" x="180" y="30"/>
<operator activated="true" class="text:filter_stopwords_english" compatibility="5.1.002" expanded="true" height="60" name="Filter Stopwords (English)" width="90" x="313" y="30"/>
<operator activated="true" class="text:generate_n_grams_terms" compatibility="5.1.002" expanded="true" height="60" name="Generate n-Grams (Terms)" width="90" x="514" y="120"/>
<connect from_port="document" to_op="Tokenize (2)" to_port="document"/>
<connect from_op="Tokenize (2)" from_port="document" to_op="Transform Cases (2)" to_port="document"/>
<connect from_op="Transform Cases (2)" from_port="document" to_op="Filter Stopwords (English)" to_port="document"/>
<connect from_op="Filter Stopwords (English)" 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="k_means" compatibility="5.1.011" expanded="true" height="76" name="Clustering" width="90" x="305" y="84"/>
<connect from_op="Process Documents from Files (2)" from_port="example set" to_op="Clustering" to_port="example set"/>
<connect from_op="Clustering" from_port="cluster model" to_port="result 1"/>
<connect from_op="Clustering" from_port="clustered set" 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>