bioNLP-UNAM / useless

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Ignacio Arroyo Fernández
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......@@ -8,8 +8,8 @@ The main method follows the next pipeline:
- Parse abstracts from two input files (classA and classB; see files format at the `data/` directory)
- Transform abstracts into their TFIDF sparse representations
- Train Support Vector Machines with different parameters by using GridSearch
- Select the best estimator and save it at `model/svm_model.pkl` (default)
- Save TFIDF transformation for keeping the training vocabulary (stored at `model/tfidf_model.pkl`)
- Select the best estimator and save it at `model_binClass/svm_model.pkl` (default)
- Save TFIDF transformation for keeping the training vocabulary (stored at `model_binClass/tfidf_model.pkl`)
### Prediction mode
- Parse abstracts from a unique input file
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