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senpy/example-plugins/sklearn/mypipeline.py
J. Fernando Sánchez 1087692de2 Add sklearn
* Add sklearn example
* Fix test_case
* Add SenpyClientUse docs

a.k.a. The wise men edition
2018-01-07 23:02:38 +01:00

31 lines
1023 B
Python

from sklearn.pipeline import Pipeline
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.model_selection import train_test_split
from mydata import text, labels
X_train, X_test, y_train, y_test = train_test_split(text, labels, test_size=0.12, random_state=42)
from sklearn.naive_bayes import MultinomialNB
count_vec = CountVectorizer(tokenizer=lambda x: x.split())
clf3 = MultinomialNB()
pipeline = Pipeline([('cv', count_vec),
('clf', clf3)])
pipeline.fit(X_train, y_train)
print('Feature names: {}'.format(count_vec.get_feature_names()))
print('Class count: {}'.format(clf3.class_count_))
if __name__ == '__main__':
print('--Results--')
tests = [
(['The sentiment for senpy should be positive :)', ], 1),
(['The sentiment for anything else should be negative :()', ], -1)
]
for features, expected in tests:
result = pipeline.predict(features)
print('Input: {}\nExpected: {}\nGot: {}'.format(features[0], expected, result))