"Exception: java.lang.NullPointerException while clustering - More help please."

Diana_Wegner

I am new to both data mining and RM, and was able to get started very quickly on a simple text mining problem.  I ran into problems once I started clustering.  I have almost 3000 text strings to cluster and none are blank.  Each has a unique ID and a description.  I'm getting the following error...

Exception: java.lang.NullPointerException error.

I tried re-installing the software per a previously reported issue, but that didn't help.  I turned on debugging, but the trace is not helping me either.  When I click "send bug report", I get the following error...

Cannot connect to BugZilla server.  Please check your internet connection and try again.  

My internet works fine (I'm able to run "updates and extensions" for example)

Here is my xml...

<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="5.3.013">
 <context>
   <input/>
   <output>
     <location>//Local Repository/Result 1 Process Document Cluster</location>
     <location>//Local Repository/Result 2 clustering</location>
     <location>//Local Repository/Result 3</location>
   </output>
   <macros/>
 </context>
 <operator activated="true" class="process" compatibility="5.3.013" expanded="true" name="Process">
   <process expanded="true">
     <operator activated="true" class="read_csv" compatibility="5.3.013" expanded="true" height="60" name="Read CSV" width="90" x="179" y="210">
       <parameter key="csv_file" value="C:\Users\lzd3rc\Documents\ADM - Project Files\CrowdSourcing\data mining clustingering trustworthiness\innovation network\AQA Miner\rapidminer\GATS Input File 7 rapidminder SMALL.csv"/>
       <parameter key="column_separators" value=","/>
       <parameter key="first_row_as_names" value="false"/>
       <list key="annotations">
         <parameter key="0" value="Name"/>
       </list>
       <parameter key="encoding" value="windows-1252"/>
       <list key="data_set_meta_data_information">
         <parameter key="0" value="UNIQID.true.text.label"/>
         <parameter key="1" value="EXP1.true.text.attribute"/>
       </list>
     </operator>
     <operator activated="true" class="text:process_document_from_data" compatibility="5.3.002" expanded="true" height="76" name="Process Documents from Data" width="90" x="380" y="165">
       <parameter key="create_word_vector" value="false"/>
       <parameter key="add_meta_information" value="false"/>
       <parameter key="keep_text" value="true"/>
       <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">
         <operator activated="true" class="text:tokenize" compatibility="5.3.002" expanded="true" height="60" name="Tokenize (2)" width="90" x="45" y="30"/>
         <operator activated="true" class="text:transform_cases" compatibility="5.3.002" expanded="true" height="60" name="Transform Cases (2)" width="90" x="179" y="30"/>
         <operator activated="true" class="text:filter_stopwords_english" compatibility="5.3.002" expanded="true" height="60" name="Filter Stopwords (2)" width="90" x="313" y="30"/>
         <operator activated="true" class="text:filter_by_length" compatibility="5.3.002" expanded="true" height="60" name="Filter Tokens (by Length)" width="90" x="447" y="75">
           <parameter key="min_chars" value="2"/>
           <parameter key="max_chars" value="99999"/>
         </operator>
         <operator activated="true" class="text:generate_n_grams_terms" compatibility="5.3.002" expanded="true" height="60" name="Generate n-Grams (Terms)" width="90" x="581" y="75">
           <parameter key="max_length" value="3"/>
         </operator>
         <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 (2)" to_port="document"/>
         <connect from_op="Filter Stopwords (2)" 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="fast_k_means" compatibility="5.3.013" expanded="true" height="76" name="Clustering" width="90" x="514" y="300">
       <parameter key="k" value="5"/>
       <parameter key="determine_good_start_values" value="true"/>
     </operator>
     <connect from_op="Read CSV" 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="Clustering" to_port="example set"/>
     <connect from_op="Process Documents from Data" from_port="word list" to_port="result 1"/>
     <connect from_op="Clustering" from_port="cluster model" 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>


Any help is appriciated.  Thanks!!

Marco_Boeck

Hi,

thank you for the report! I've added it to our internal bug tracker.

Regards,
Marco

land

Hi Diane,

although this is a user unfriendly bug, that is occurring in your situation, this only results from a wrongly set Process Documents Operator. You de-selected the parameter "create word vector". This results in an ExampleSet without any columns, with the exception of the text column, which is special. K-Means should be able to give a proper error message, however, it can't run in this situation.

To solve this problem, simply enable the creation of the word vectors in the parameters of Process Documents from Data.

Greetings,
  Sebastian

Diana_Wegner

Thank you for the quick response!  K-means now runs.   

However, there is a follow-up question.  K-means, like many of the other clustering modules, places all 3000 records in one cluster.  I've tried different parameters with no luck.  Do you have any hints to resolve this issue?

Again, thanks for your help!

Diana