init learning cats

classify_mail.py

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+from sklearn.feature_extraction.text import TfidfTransformer,CountVectorizer
+from sklearn.feature_extraction import DictVectorizer
+from sklearn.naive_bayes import MultinomialNB
+from sklearn.pipeline import Pipeline, FeatureUnion
+import sys
+import yaml
+from sklearn.preprocessing import OneHotEncoder
+from sklearn.preprocessing import LabelEncoder
+
+
+text_clf = Pipeline([('vect', CountVectorizer()),('tfidf', TfidfTransformer()),('clf', MultinomialNB())])
+
+text_ohc = Pipeline([('ohc', OneHotEncoder()),('clf', MultinomialNB())])
+
+combined_features = FeatureUnion([('vect1', CountVectorizer()),('vect2', CountVectorizer())])
+
+
+enc=OneHotEncoder()
+with open("example_1.yaml", 'r') as stream:
+    try:
+        train=yaml.safe_load(stream)
+    except yaml.YAMLError as exc:
+        print(exc)
+
+tc=text_clf.fit(train["data"],train["target"])