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TEXT MINING HELP!!!!!!!
HEY GUYS,
I USE RAPID MINER FOR TEXT MINING.WHEN I TRY TO PUT TRANFORM CASES OR GENERATE N GRAMS IN THE PROCCES, THE PROJECT DON'T RUN. I USE NAIVE BAYES IN VALIDATION AND WITHOUT TRANFORM CASES AND GENERATE N GRAMS I HAVE ONLY 67% PRFORMANCE.I DID TO GO TO 75%.WHAT I MUST TO DO TO RUN WITHOUT PROBLEMS??HERE IS THE XML OF THE PROCCES.IF A DELETE TRANFORM CASES ITS RUN AND HAVE 68%.SORRY FOR THE BAD ENGLISH,HOPE TO UNDERSTAND.PLS HELP!!!!
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="5.1.006">
<context>
<input/>
<output/>
<macros/>
</context>
<operator activated="true" class="process" compatibility="5.1.006" expanded="true" name="Process">
<parameter key="parallelize_main_process" value="true"/>
<process expanded="true" height="396" width="660">
<operator activated="true" class="text:process_document_from_file" compatibility="5.1.001" expanded="true" height="76" name="Process Documents from Files" width="90" x="45" y="75">
<list key="text_directories">
<parameter key="negative" value="C:\Users\Alkis\Desktop\DATA_MINIMG\Negative"/>
<parameter key="positive" value="C:\Users\Alkis\Desktop\DATA_MINIMG\positive"/>
</list>
<parameter key="vector_creation" value="Binary Term Occurrences"/>
<parameter key="prune_above_percent" value="99.0"/>
<parameter key="parallelize_vector_creation" value="true"/>
<process expanded="true" height="396" width="815">
<operator activated="true" class="text:tokenize" compatibility="5.1.001" expanded="true" height="60" name="Tokenize" width="90" x="112" y="120"/>
<operator activated="true" class="text:transform_cases" compatibility="5.1.001" expanded="true" height="60" name="Transform Cases" width="90" x="299" y="124"/>
<operator activated="true" class="text:generate_n_grams_terms" compatibility="5.1.001" expanded="true" height="60" name="Generate n-Grams (Terms)" width="90" x="413" y="121"/>
<operator activated="true" class="text:filter_stopwords_dictionary" compatibility="5.1.001" expanded="true" height="60" name="Filter Stopwords (Dictionary)" width="90" x="581" y="120">
<parameter key="file" value="C:\Users\Alkis\Desktop\DATA_MINIMG\stopwords_greek\stopwords_greek.txt"/>
</operator>
<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="Generate n-Grams (Terms)" to_port="document"/>
<connect from_op="Generate n-Grams (Terms)" from_port="document" to_op="Filter Stopwords (Dictionary)" to_port="document"/>
<connect from_op="Filter Stopwords (Dictionary)" 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="x_validation" compatibility="5.1.006" expanded="true" height="112" name="Validation" width="90" x="246" y="75">
<description>A cross-validation evaluating a decision tree model.</description>
<parameter key="parallelize_training" value="true"/>
<parameter key="parallelize_testing" value="true"/>
<process expanded="true" height="654" width="466">
<operator activated="true" class="naive_bayes" compatibility="5.1.006" expanded="true" height="76" name="Naive Bayes" width="90" x="160" y="196"/>
<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="654" width="466">
<operator activated="true" class="apply_model" compatibility="5.1.006" expanded="true" height="76" name="Apply Model" width="90" x="45" y="30">
<list key="application_parameters"/>
</operator>
<operator activated="true" class="performance" compatibility="5.1.006" 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="sink_averagable 1" spacing="0"/>
<portSpacing port="sink_averagable 2" spacing="0"/>
</process>
</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="Validation" to_port="training"/>
<connect from_op="Process Documents from Files" from_port="word list" to_port="result 2"/>
<connect from_op="Validation" from_port="averagable 1" to_port="result 1"/>
<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>
I USE RAPID MINER FOR TEXT MINING.WHEN I TRY TO PUT TRANFORM CASES OR GENERATE N GRAMS IN THE PROCCES, THE PROJECT DON'T RUN. I USE NAIVE BAYES IN VALIDATION AND WITHOUT TRANFORM CASES AND GENERATE N GRAMS I HAVE ONLY 67% PRFORMANCE.I DID TO GO TO 75%.WHAT I MUST TO DO TO RUN WITHOUT PROBLEMS??HERE IS THE XML OF THE PROCCES.IF A DELETE TRANFORM CASES ITS RUN AND HAVE 68%.SORRY FOR THE BAD ENGLISH,HOPE TO UNDERSTAND.PLS HELP!!!!
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="5.1.006">
<context>
<input/>
<output/>
<macros/>
</context>
<operator activated="true" class="process" compatibility="5.1.006" expanded="true" name="Process">
<parameter key="parallelize_main_process" value="true"/>
<process expanded="true" height="396" width="660">
<operator activated="true" class="text:process_document_from_file" compatibility="5.1.001" expanded="true" height="76" name="Process Documents from Files" width="90" x="45" y="75">
<list key="text_directories">
<parameter key="negative" value="C:\Users\Alkis\Desktop\DATA_MINIMG\Negative"/>
<parameter key="positive" value="C:\Users\Alkis\Desktop\DATA_MINIMG\positive"/>
</list>
<parameter key="vector_creation" value="Binary Term Occurrences"/>
<parameter key="prune_above_percent" value="99.0"/>
<parameter key="parallelize_vector_creation" value="true"/>
<process expanded="true" height="396" width="815">
<operator activated="true" class="text:tokenize" compatibility="5.1.001" expanded="true" height="60" name="Tokenize" width="90" x="112" y="120"/>
<operator activated="true" class="text:transform_cases" compatibility="5.1.001" expanded="true" height="60" name="Transform Cases" width="90" x="299" y="124"/>
<operator activated="true" class="text:generate_n_grams_terms" compatibility="5.1.001" expanded="true" height="60" name="Generate n-Grams (Terms)" width="90" x="413" y="121"/>
<operator activated="true" class="text:filter_stopwords_dictionary" compatibility="5.1.001" expanded="true" height="60" name="Filter Stopwords (Dictionary)" width="90" x="581" y="120">
<parameter key="file" value="C:\Users\Alkis\Desktop\DATA_MINIMG\stopwords_greek\stopwords_greek.txt"/>
</operator>
<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="Generate n-Grams (Terms)" to_port="document"/>
<connect from_op="Generate n-Grams (Terms)" from_port="document" to_op="Filter Stopwords (Dictionary)" to_port="document"/>
<connect from_op="Filter Stopwords (Dictionary)" 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="x_validation" compatibility="5.1.006" expanded="true" height="112" name="Validation" width="90" x="246" y="75">
<description>A cross-validation evaluating a decision tree model.</description>
<parameter key="parallelize_training" value="true"/>
<parameter key="parallelize_testing" value="true"/>
<process expanded="true" height="654" width="466">
<operator activated="true" class="naive_bayes" compatibility="5.1.006" expanded="true" height="76" name="Naive Bayes" width="90" x="160" y="196"/>
<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="654" width="466">
<operator activated="true" class="apply_model" compatibility="5.1.006" expanded="true" height="76" name="Apply Model" width="90" x="45" y="30">
<list key="application_parameters"/>
</operator>
<operator activated="true" class="performance" compatibility="5.1.006" 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="sink_averagable 1" spacing="0"/>
<portSpacing port="sink_averagable 2" spacing="0"/>
</process>
</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="Validation" to_port="training"/>
<connect from_op="Process Documents from Files" from_port="word list" to_port="result 2"/>
<connect from_op="Validation" from_port="averagable 1" to_port="result 1"/>
<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>
0
Answers
yeeees, transform cases always helps, anytime.
So what the hack is the error? You will have to give me some HINTS what goes wrong before I can help you fix it. Your process looks fine.
Greetings,
Sebastian
May 17, 2011 6:46:41 PM INFO: Process //NewLocalRepository/TEST_ME)POLLA starts
May 17, 2011 6:46:41 PM INFO: Executing process concurrently: Main Process
May 17, 2011 6:46:41 PM INFO: Executing process concurrently: Vector Creation
May 17, 2011 6:46:41 PM INFO: Executing process concurrently: Vector Creation
May 17, 2011 6:46:41 PM INFO: Executing process concurrently: Vector Creation
May 17, 2011 6:46:41 PM WARNING: Caught exception in concurrent execution of Transform Cases (Transform Cases): java.lang.NullPointerException
May 17, 2011 6:46:41 PM WARNING: Caught exception in concurrent execution of Process Documents from Files (Process Documents from Files): java.lang.NullPointerException
And i have the same with N grams :
May 17, 2011 6:51:58 PM INFO: Executing process concurrently: Vector Creation
May 17, 2011 6:51:58 PM WARNING: Caught exception in concurrent execution of Generate n-Grams (Terms) (Generate n-Grams (Terms)): java.lang.NullPointerException
May 17, 2011 6:51:58 PM WARNING: Caught exception in concurrent execution of Process Documents from Files (Process Documents from Files): java.lang.NullPointerException
i; mnew in rapid miner and i dont know how to fix it.if you know any other operators(like tranform cases)that could help me to go to 75% or 72% please let me know,
Thanks for the reply...!!!!
please send me the stack trace of the error. There seems to be a problem, but without the stack trace I don't know where.
Greetings,
Sebastian
thanks again Sebasntian