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"How to USE Performance Operator on Text Mining Root Process"


Can you Suggest which performance operator work fine for my text mining project.I'm looking for a performance operator which can give me a measure of accuracy and precision for my classification model.
Below is the XML code:
<operator name="Root" class="Process" expanded="yes">
<operator name="OperatorChain" class="OperatorChain" expanded="yes">
<operator name="TextInput" class="TextInput" expanded="no">
<list key="texts">
<parameter key="Price" value="C:\Documents and Settings\munish.virang\Desktop\XMX\BARCLAYSBANK\PRICE"/>
<parameter key="Process" value="C:\Documents and Settings\munish.virang\Desktop\XMX\BARCLAYSBANK\PROCESS"/>
<parameter key="Product" value="C:\Documents and Settings\munish.virang\Desktop\SAMPLE_DATA_SET\BARCLAYSBANK\PRODUCT"/>
<parameter key="Promotion" value="C:\Documents and Settings\munish.virang\Desktop\SAMPLE_DATA_SET\BARCLAYSBANK\PROMOTION"/>
</list>
<parameter key="output_word_list" value="C:\Documents and Settings\munish.virang\Desktop\XMX\BARCLAYSBANK\words.list"/>
<list key="namespaces">
</list>
<parameter key="create_text_visualizer" value="true"/>
<operator name="StringTokenizer" class="StringTokenizer">
</operator>
<operator name="EnglishStopwordFilter" class="EnglishStopwordFilter">
</operator>
<operator name="TokenLengthFilter" class="TokenLengthFilter">
<parameter key="min_chars" value="3"/>
</operator>
<operator name="LovinsStemmer" class="LovinsStemmer">
</operator>
</operator>
<operator name="LibSVMLearner" class="LibSVMLearner">
<list key="class_weights">
</list>
<parameter key="calculate_confidences" value="true"/>
</operator>
<operator name="ModelWriter" class="ModelWriter">
<parameter key="model_file" value="C:\Documents and Settings\munish.virang\Desktop\XMX\BARCLAYSBANK\SVM.mod"/>
</operator>
</operator>
<operator name="OperatorChain (2)" class="OperatorChain" expanded="yes">
<operator name="TextInput (2)" class="TextInput" expanded="no">
<list key="texts">
<parameter key="PRODUCT" value="C:\Documents and Settings\munish.virang\Desktop\XMX\BARCLAYSBANK\PRODUCT"/>
</list>
<parameter key="input_word_list" value="C:\Documents and Settings\munish.virang\Desktop\XMX\BARCLAYSBANK\words.list"/>
<list key="namespaces">
</list>
<parameter key="create_text_visualizer" value="true"/>
<operator name="StringTokenizer (2)" class="StringTokenizer">
</operator>
<operator name="EnglishStopwordFilter (2)" class="EnglishStopwordFilter">
</operator>
<operator name="TokenLengthFilter (2)" class="TokenLengthFilter">
<parameter key="min_chars" value="3"/>
</operator>
<operator name="LovinsStemmer (2)" class="LovinsStemmer">
</operator>
</operator>
<operator name="ModelLoader" class="ModelLoader">
<parameter key="model_file" value="C:\Documents and Settings\munish.virang\Desktop\XMX\BARCLAYSBANK\SVM.mod"/>
</operator>
<operator name="ModelApplier" class="ModelApplier">
<list key="application_parameters">
</list>
</operator>
</operator>
</operator>
Below is the XML code:
<operator name="Root" class="Process" expanded="yes">
<operator name="OperatorChain" class="OperatorChain" expanded="yes">
<operator name="TextInput" class="TextInput" expanded="no">
<list key="texts">
<parameter key="Price" value="C:\Documents and Settings\munish.virang\Desktop\XMX\BARCLAYSBANK\PRICE"/>
<parameter key="Process" value="C:\Documents and Settings\munish.virang\Desktop\XMX\BARCLAYSBANK\PROCESS"/>
<parameter key="Product" value="C:\Documents and Settings\munish.virang\Desktop\SAMPLE_DATA_SET\BARCLAYSBANK\PRODUCT"/>
<parameter key="Promotion" value="C:\Documents and Settings\munish.virang\Desktop\SAMPLE_DATA_SET\BARCLAYSBANK\PROMOTION"/>
</list>
<parameter key="output_word_list" value="C:\Documents and Settings\munish.virang\Desktop\XMX\BARCLAYSBANK\words.list"/>
<list key="namespaces">
</list>
<parameter key="create_text_visualizer" value="true"/>
<operator name="StringTokenizer" class="StringTokenizer">
</operator>
<operator name="EnglishStopwordFilter" class="EnglishStopwordFilter">
</operator>
<operator name="TokenLengthFilter" class="TokenLengthFilter">
<parameter key="min_chars" value="3"/>
</operator>
<operator name="LovinsStemmer" class="LovinsStemmer">
</operator>
</operator>
<operator name="LibSVMLearner" class="LibSVMLearner">
<list key="class_weights">
</list>
<parameter key="calculate_confidences" value="true"/>
</operator>
<operator name="ModelWriter" class="ModelWriter">
<parameter key="model_file" value="C:\Documents and Settings\munish.virang\Desktop\XMX\BARCLAYSBANK\SVM.mod"/>
</operator>
</operator>
<operator name="OperatorChain (2)" class="OperatorChain" expanded="yes">
<operator name="TextInput (2)" class="TextInput" expanded="no">
<list key="texts">
<parameter key="PRODUCT" value="C:\Documents and Settings\munish.virang\Desktop\XMX\BARCLAYSBANK\PRODUCT"/>
</list>
<parameter key="input_word_list" value="C:\Documents and Settings\munish.virang\Desktop\XMX\BARCLAYSBANK\words.list"/>
<list key="namespaces">
</list>
<parameter key="create_text_visualizer" value="true"/>
<operator name="StringTokenizer (2)" class="StringTokenizer">
</operator>
<operator name="EnglishStopwordFilter (2)" class="EnglishStopwordFilter">
</operator>
<operator name="TokenLengthFilter (2)" class="TokenLengthFilter">
<parameter key="min_chars" value="3"/>
</operator>
<operator name="LovinsStemmer (2)" class="LovinsStemmer">
</operator>
</operator>
<operator name="ModelLoader" class="ModelLoader">
<parameter key="model_file" value="C:\Documents and Settings\munish.virang\Desktop\XMX\BARCLAYSBANK\SVM.mod"/>
</operator>
<operator name="ModelApplier" class="ModelApplier">
<list key="application_parameters">
</list>
</operator>
</operator>
</operator>
Tagged:
0
Answers
why can't you use one of the regular performance evaluators? Check ClassificationPerformance, BinominalPerformance, Performance, and PerformanceEvaluator.
Besides, I am not sure why you are choosing such a complicated process setup. There is no need to save your model if all you want to do is apply it on a different data set later. You probably also want to wrap your evaluation into a XValidation. Have a look at the samples.
Best,
Simon