forked from kubapok/retroc2
minor fix
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7c67f8511a
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418816f27e
@ -13,8 +13,8 @@ def linear_regression():
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colnames_test = ['data']
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train = pd.read_csv("train/train.tsv", names = colnames_train, sep = "\t")
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dev_0 = pd.read_csv("dev-0/in.tsv", error_bad_lines = False, header = None, sep = "\t")
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dev_1 = pd.read_csv("dev-1/in.tsv", error_bad_lines = False, header = None, sep = "\t")
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dev_0 = pd.read_csv("dev-0/in.tsv", error_bad_lines = False, header = None, sep = "\t", quoting=csv.QUOTE_NONE)
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dev_1 = pd.read_csv("dev-1/in.tsv", error_bad_lines = False, header = None, sep = "\t", quoting=csv.QUOTE_NONE,)
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test = pd.read_csv("test-A/in.tsv", names = colnames_test, sep = "\t")
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# stworzenie instancji TFIDF i regresji liniowej
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@ -29,14 +29,14 @@ def linear_regression():
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lin_reg.fit(train_vec, date)
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# predykcja dla dev-0
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evaluate_dev = tf(dev_0['data'])
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evaluate_dev = tf.transform(dev_0['data'])
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prediction_dev = lin_reg.predict(evaluate_dev)
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pd.DataFrame(prediction_dev).to_csv('dev-0/out.tsv', sep = "\t", index = False, header = False)
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pd.DataFrame(prediction_dev).to_csv('dev-0/out2.tsv', sep = "\t", index = False, header = False)
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# predykcja dla test-A
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evaluate_test = tf(test['data'])
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evaluate_test = tf.transform(test['data'])
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prediction_test = lin_reg.predict(evaluate_test)
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pd.DataFrame(prediction_test).to_csv('test-A/out.tsv', sep = "\t", index = False, header = False)
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pd.DataFrame(prediction_test).to_csv('test-A/out2.tsv', sep = "\t", index = False, header = False)
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return None
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