Text Mining - Unnammed error in Apply Model (Documents) Operator
Titzaaa
New Altair Community Member
Dear community,
this is the first time I try to build a text mining process and I cannot find my mistake: When trying to run the process, I get a error message saying "unnamed error. no message". Can you help?
Here is my code:
this is the first time I try to build a text mining process and I cannot find my mistake: When trying to run the process, I get a error message saying "unnamed error. no message". Can you help?
Here is my code:
<?xml version="1.0" encoding="UTF-8"?><process version="9.3.000"> <context> <input/> <output/> <macros/> </context> <operator activated="true" class="process" compatibility="9.3.000" expanded="true" name="Process"> <parameter key="logverbosity" value="init"/> <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="retrieve" compatibility="9.3.000" expanded="true" height="68" name="Retrieve" width="90" x="45" y="34"> <parameter key="repository_entry" value="//Masterarbeit/Data/Finanzen.net"/> </operator> <operator activated="true" class="nominal_to_text" compatibility="9.3.000" expanded="true" height="82" name="Nominal to Text" width="90" x="179" y="34"> <parameter key="attribute_filter_type" value="single"/> <parameter key="attribute" value="Titel"/> <parameter key="attributes" value=""/> <parameter key="use_except_expression" value="false"/> <parameter key="value_type" value="nominal"/> <parameter key="use_value_type_exception" value="false"/> <parameter key="except_value_type" value="file_path"/> <parameter key="block_type" value="single_value"/> <parameter key="use_block_type_exception" value="false"/> <parameter key="except_block_type" value="single_value"/> <parameter key="invert_selection" value="false"/> <parameter key="include_special_attributes" value="false"/> </operator> <operator activated="true" class="text:process_document_from_data" compatibility="8.2.000" expanded="true" height="82" name="Process Documents from Data" width="90" x="380" y="34"> <parameter key="create_word_vector" value="true"/> <parameter key="vector_creation" value="Binary Term Occurrences"/> <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"/> <parameter key="select_attributes_and_weights" value="false"/> <list key="specify_weights"/> <process expanded="true"> <operator activated="true" class="text:tokenize" compatibility="8.2.000" expanded="true" height="68" name="Tokenize" width="90" x="179" 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="8.2.000" expanded="true" height="68" name="Transform Cases" width="90" x="313" y="34"> <parameter key="transform_to" value="lower case"/> </operator> <operator activated="true" class="text:filter_stopwords_german" compatibility="8.2.000" expanded="true" height="68" name="Filter Stopwords (German)" width="90" x="447" y="34"> <parameter key="stop_word_list" value="Standard"/> </operator> <operator activated="true" class="text:filter_by_length" compatibility="8.2.000" expanded="true" height="68" name="Filter Tokens (by Length)" width="90" x="648" y="34"> <parameter key="min_chars" value="3"/> <parameter key="max_chars" value="10000"/> </operator> <operator activated="false" class="text:generate_n_grams_terms" compatibility="8.2.000" expanded="true" height="68" name="Generate n-Grams (Terms)" width="90" x="246" y="238"> <parameter key="max_length" value="2"/> </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="Filter Stopwords (German)" to_port="document"/> <connect from_op="Filter Stopwords (German)" from_port="document" to_op="Filter Tokens (by Length)" to_port="document"/> <connect from_op="Filter Tokens (by Length)" 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="retrieve" compatibility="9.3.000" expanded="true" height="68" name="Retrieve GRESD" width="90" x="45" y="238"> <parameter key="repository_entry" value="../Data/GRESD"/> </operator> <operator activated="true" class="retrieve" compatibility="9.3.000" expanded="true" height="68" name="Retrieve Negationsliste" width="90" x="45" y="391"> <parameter key="repository_entry" value="../Data/Negationsliste"/> </operator> <operator activated="true" class="operator_toolbox:dictionary_sentiment_learner" compatibility="2.0.001" expanded="true" height="82" name="Dictionary-Based Sentiment (Documents)" width="90" x="246" y="289"> <parameter key="value_attribute" value="Klassifizierung"/> <parameter key="key_attribute" value="Wort"/> <parameter key="negation_attribute" value="Negationen"/> <parameter key="negation_window_size" value="1"/> <parameter key="use_symmetric_negation_window" value="false"/> </operator> <operator activated="true" class="text:data_to_documents" compatibility="8.2.000" expanded="true" height="68" name="Data to Documents" width="90" x="514" y="85"> <parameter key="select_attributes_and_weights" value="false"/> <list key="specify_weights"/> </operator> <operator activated="true" class="operator_toolbox:apply_model_documents" compatibility="2.0.001" expanded="true" height="103" name="Apply Model (Documents)" width="90" x="447" y="289"> <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" to_port="example set"/> <connect from_op="Process Documents from Data" from_port="example set" to_op="Data to Documents" to_port="example set"/> <connect from_op="Retrieve GRESD" from_port="output" to_op="Dictionary-Based Sentiment (Documents)" to_port="exa"/> <connect from_op="Retrieve Negationsliste" from_port="output" to_op="Dictionary-Based Sentiment (Documents)" to_port="neg"/> <connect from_op="Dictionary-Based Sentiment (Documents)" from_port="mod" to_op="Apply Model (Documents)" to_port="mod"/> <connect from_op="Data to Documents" from_port="documents" to_op="Apply Model (Documents)" to_port="doc"/> <connect from_op="Apply Model (Documents)" from_port="exa" 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>
Thanks a lot on advance!
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Best Answer
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Hi,good one. not sure what i mixed up there. Any chance you can share the data (privatly)? Feel free to connect with me via mschmitz at rapidminer dot com. Feel free to use germanCheers,Martin1
Answers
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Hi,good one. not sure what i mixed up there. Any chance you can share the data (privatly)? Feel free to connect with me via mschmitz at rapidminer dot com. Feel free to use germanCheers,Martin1
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Hi @Titzaaa - this is MarlaBot. I found these great videos on our RapidMiner Academy that you may find helpful:
MarlaBot0