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<operator name="Root" class="Process" expanded="yes"> <description text="#ylt#h3#ygt#Loading and applying a text classifier#ylt#/h3#ygt##ylt#p#ygt#This experiments shows how to load a text classifier and how to apply it a new set of texts.#ylt#/p#ygt##ylt#p#ygt##ylt#b#ygt#Important note:#ylt#/b#ygt#You have to load the wordlist stored in the experiment that created the text classification model. Otherwise, the TextInput will not know which dimensions to use for the vector space and the learned model and the new text representations will not match. #ylt#/p#ygt#"/> <operator name="TextInput" class="TextInput" expanded="yes"> <list key="texts"> <parameter key="graphics" value="../data/newsgroup/graphics"/> </list> <parameter key="default_content_language" value="english"/> <parameter key="input_word_list" value="../data/training_words.list"/> <list key="namespaces"> </list> <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="PorterStemmer" class="PorterStemmer"> </operator> </operator> <operator name="ModelLoader" class="ModelLoader"> <parameter key="model_file" value="../data/training_model.mod"/> </operator> <operator name="ModelApplier" class="ModelApplier"> <list key="application_parameters"> </list> </operator> <operator name="AttributeFilter" class="AttributeFilter"> <parameter key="condition_class" value="attribute_name_filter"/> <parameter key="parameter_string" value=".*"/> <parameter key="invert_filter" value="true"/> </operator> <operator name="ExcelExampleSetWriter" class="ExcelExampleSetWriter"> <parameter key="excel_file" value="C:\Documents and Settings\matthew_garong\My Documents\Matthew\TM_Workspace\rapidminer-text-4.4-examples\04_Learning\apply_output_temp.xls"/> </operator></operator>
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