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This project is a simple ruby gem that provide a way to transform a text into sparse features vector using libsvm/liblinear format (http://www.csie.ntu.edu.tw/~cjlin/libsvm).
Since this tool is thought to be used with short-text it provides only binary representations of tokens.
% libsvm_pp --help
libsvm_pp [options] <filename>
-m, --mode [TYPE] Select unigram (default)/bigram/trigrams
-s, --stemming Use this you want stemming
-w, --remove-stopwords Use this if you want remove stopwords
-t, --testing Use this to use testing mode
-l, --language [TYPE] Select your language it / en
-n N Numeric type
-o [output] output file
It is possible to use the library following these steps:
require "libsvm_preprocessor/preprocesso"
[…]
preprocessor = Preprocessor.new(numeric_type: i)
preprocessor.use("TRAIN.csv", "TRAIN.svm")
preprocessor.use("TEST.csv", "TEST.svm", testing: true)
In this case TRAIN.svm will contain your training set and TEST.svm will contain the testing set.
This project is far to be complete, as soon as possible I will provide a better documentation.
FAQs
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We found that libsvm_preprocessor demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
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