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fenago
50 lines
1.4 KiB
Python
50 lines
1.4 KiB
Python
import unittest
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import import_ipynb
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import pandas as pd
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import pandas.testing as pd_testing
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import numpy.testing as np_testing
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import pandas as pd
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from sklearn.model_selection import train_test_split
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from sklearn.ensemble import RandomForestRegressor
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class Test(unittest.TestCase):
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def setUp(self):
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import Exercise9_05
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self.exercises = Exercise9_05
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self.file_url = '../Dataset/phpYYZ4Qc.csv'
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self.df = pd.read_csv(self.file_url)
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self.df.head()
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self.y = self.df.pop('rej')
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self.X_train, self.X_test, self.y_train, self.y_test = train_test_split(self.df, self.y, test_size=0.3, random_state=1)
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self.rf_model = RandomForestRegressor(random_state=1, n_estimators=50, max_depth=6, min_samples_leaf=60)
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self.rf_model.fit(self.X_train, self.y_train)
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def test_file_url(self):
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self.assertEqual(self.exercises.file_url, self.file_url)
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def test_df(self):
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pd_testing.assert_frame_equal(self.exercises.df, self.df)
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def test_y(self):
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np_testing.assert_array_equal(self.exercises.y , self.y)
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def test_X_train(self):
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np_testing.assert_array_equal(self.exercises.X_train , self.X_train)
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def test_X_test(self):
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np_testing.assert_array_equal(self.exercises.X_test, self.X_test)
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def test_y_train(self):
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np_testing.assert_array_equal(self.exercises.y_train , self.y_train)
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def test_y_test(self):
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np_testing.assert_array_equal(self.exercises.y_test , self.y_test)
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if __name__ == '__main__':
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unittest.main()
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