Entropy and purity of k-means ?
Learner IIHello,
I have 11 docuemtns which contains unstractiured data. I am using k-means to cluster these documents into 3 clusters. How to validate the k-means using Entropy and Purity ?
Is there any direct operater to use and get the real values of Entropy and Purity?
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XML file:
<?xml version="1.0" encoding="UTF-8"?><process version="7.6.003">
<context>
<input/>
<output/>
<macros/>
</context>
<operator activated="true" class="process" compatibility="7.6.003" expanded="true" name="Process">
<parameter key="logverbosity" value="all"/>
<parameter key="random_seed" value="2001"/>
<parameter key="send_mail" value="never"/>
<parameter key="notification_email" value=""/>
<parameter key="process_duration_for_mail" value="30"/>
<parameter key="encoding" value="SYSTEM"/>
<process expanded="true">
<operator activated="true" class="text:process_document_from_file" compatibility="7.5.000" expanded="true" height="82" name="Process Documents from Files" width="90" x="45" y="34">
<list key="text_directories">
<parameter key="doc1" value="C:\Papidminer_Data_tags1\doc1"/>
<parameter key="doc2" value="C:\Papidminer_Data_tags1\doc2"/>
<parameter key="doc3" value="C:\Papidminer_Data_tags1\doc3"/>
<parameter key="doc4" value="C:\Papidminer_Data_tags1\doc4"/>
<parameter key="doc5" value="C:\Papidminer_Data_tags1\doc5"/>
<parameter key="doc6" value="C:\Papidminer_Data_tags1\doc6"/>
<parameter key="doc7" value="C:\Papidminer_Data_tags1\doc7"/>
<parameter key="doc7" value="C:\Papidminer_Data_tags1\doc7"/>
<parameter key="doc8" value="C:\Papidminer_Data_tags1\doc8"/>
<parameter key="doc9" value="C:\Papidminer_Data_tags1\doc9"/>
<parameter key="doc10" value="C:\Papidminer_Data_tags1\doc10"/>
<parameter key="doc11" value="C:\Papidminer_Data_tags1\doc11"/>
</list>
<parameter key="file_pattern" value="*"/>
<parameter key="extract_text_only" value="true"/>
<parameter key="use_file_extension_as_type" value="true"/>
<parameter key="content_type" value="txt"/>
<parameter key="encoding" value="SYSTEM"/>
<parameter key="create_word_vector" value="true"/>
<parameter key="vector_creation" value="TF-IDF"/>
<parameter key="add_meta_information" value="true"/>
<parameter key="keep_text" value="false"/>
<parameter key="prune_method" value="none"/>
<parameter key="prune_below_percent" value="3.0"/>
<parameter key="prune_above_percent" value="30.0"/>
<parameter key="prune_below_rank" value="0.05"/>
<parameter key="prune_above_rank" value="0.95"/>
<parameter key="datamanagement" value="double_sparse_array"/>
<parameter key="data_management" value="auto"/>
<process expanded="true">
<operator activated="true" class="text:tokenize" compatibility="7.5.000" expanded="true" height="68" name="Tokenize" width="90" x="45" y="34">
<parameter key="mode" value="non letters"/>
<parameter key="characters" value=".:"/>
<parameter key="language" value="English"/>
<parameter key="max_token_length" value="3"/>
</operator>
<operator activated="true" class="text:transform_cases" compatibility="7.5.000" expanded="true" height="68" name="Transform Cases" width="90" x="246" y="34">
<parameter key="transform_to" value="lower case"/>
</operator>
<operator activated="true" class="text:filter_stopwords_english" compatibility="7.5.000" expanded="true" height="68" name="Filter Stopwords (English)" width="90" x="447" y="34"/>
<connect from_port="document" to_op="Tokenize" to_port="document"/>
<connect from_op="Tokenize" 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_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="7.6.003" expanded="true" height="82" name="Clustering" width="90" x="313" y="187">
<parameter key="add_cluster_attribute" value="true"/>
<parameter key="add_as_label" value="false"/>
<parameter key="remove_unlabeled" value="false"/>
<parameter key="k" value="3"/>
<parameter key="max_runs" value="10"/>
<parameter key="determine_good_start_values" value="false"/>
<parameter key="measure_types" value="BregmanDivergences"/>
<parameter key="mixed_measure" value="MixedEuclideanDistance"/>
<parameter key="nominal_measure" value="NominalDistance"/>
<parameter key="numerical_measure" value="DiceSimilarity"/>
<parameter key="divergence" value="SquaredEuclideanDistance"/>
<parameter key="kernel_type" value="radial"/>
<parameter key="kernel_gamma" value="1.0"/>
<parameter key="kernel_sigma1" value="1.0"/>
<parameter key="kernel_sigma2" value="0.0"/>
<parameter key="kernel_sigma3" value="2.0"/>
<parameter key="kernel_degree" value="3.0"/>
<parameter key="kernel_shift" value="1.0"/>
<parameter key="kernel_a" value="1.0"/>
<parameter key="kernel_b" value="0.0"/>
<parameter key="max_optimization_steps" value="100"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
</operator>
<connect from_port="input 1" to_op="Process Documents from Files" to_port="word list"/>
<connect from_op="Process Documents from Files" 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="source_input 2" 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>
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