Jadee/liblatrel
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Latent Relevance Tools (LIBLATREL) @brief: to train latent relevance model, and test given test_file @wiki: http://wiki.babel.baidu.com/twiki/bin/view/Com/Ecom/LatentRelevance @email: lichangcheng@baidu.com Training Usage: ./train [options] training_file [model_file] options: -f mode: 1 with factorization, 0 no factorizatoin (default 1) -k factorization dimension (default 3) -c regularization coefficient (default 0.1) training_file format: label \t x1 \t x2 (example: 1 \t 0.1 0.2 \t 0.3 0.1) Notice: use "-f 1" for dense vector model (word2vec, etc.). Testing Usage: ./test test_file model_file test_file format: label \t x1 \t x2 (example: 1 \t 0.1 0.2 \t 0.3 0.1) Predict results are saved in ${test_file}.res. You can run "./auc -r ${test_file}.res" to get the AUC of the test_file. For any questions and comments, please send your email to lichangcheng@baidu.com
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