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How to import and label multiple txt datas?
Hello, I have 3 folders containing txt files. Each folder represents an attribute that I would like to use for naive bayes classification.(For example folder 1 represents spam, folder 2 ham, folder 3 Neither ham/spam)
How can I import the txt files,every txt file labeled correctly and apply naive bayes on it? I already installed the text processing extension. I can import every txt file from one folder(with "process documents from files") but they aren't labeled. Thank you
How can I import the txt files,every txt file labeled correctly and apply naive bayes on it? I already installed the text processing extension. I can import every txt file from one folder(with "process documents from files") but they aren't labeled. Thank you
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Answers
There is a loop files operator that will enable you to read all the text files. I understood that you want to label all these files based on folder names. If that is correct, then you can look at the below thread where @KostasBonikos explained very well on extracting folder names and generating attributes with them
https://community.rapidminer.com/discussion/43826/loading-folder-names-for-text-processing
Hope this helps. @kayman might add more details.
Thanks
Varun
https://www.varunmandalapu.com/
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In essence all is described in the mentioned thread, use the foldername as reference, generate an attribute based on this foldername and set it to label using the role operator.