Initial commit

ML_tests/LinearRegression_tests/LinearRegression_GD.py

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+# Import folder where sorting algorithms
+import sys
+import unittest
+import numpy as np
+
+# For importing from different folders
+# OBS: This is supposed to be done with automated testing,
+# hence relative to folder we want to import from
+sys.path.append("ML/algorithms/linearregression")
+# If run from local:
+# sys.path.append('../../ML/algorithms/linearregression')
+from linear_regression_gradient_descent import LinearRegression
+
+
+class TestLinearRegression_GradientDescent(unittest.TestCase):
+    def setUp(self):
+        # test cases we want to run
+
+        self.linearReg = LinearRegression()
+        self.X1 = np.array([[0, 1, 2]])
+        self.y1 = np.array([[1, 2, 3]])
+        self.W1_correct = np.array([[1, 1]]).T
+
+        self.X2 = np.array([[0, 1]])
+        self.y2 = np.array([[1, 0]])
+        self.W2_correct = np.array([[1, -1]]).T
+
+        self.X3 = np.array([[1, 2, 3], [1, 2, 4]])
+        self.y3 = np.array([[5, 10, 18]])
+        self.W3_correct = np.array([[0, 2, 3]]).T
+
+        self.X4 = np.array([[0, 0]])
+        self.y4 = np.array([[0, 0]])
+        self.W4_correct = np.array([[0, 0]]).T
+
+        self.X5 = np.array([[0, 1, 2, 3, 4, 5]])
+        self.y5 = np.array([[0, 0.99, 2.01, 2.99, 4.01, 4.99]])
+        self.W5_correct = np.array([[0, 1]]).T
+
+    def test_perfectpositiveslope(self):
+        W = self.linearReg.main(self.X1, self.y1)
+        boolean_array = np.isclose(W, self.W1_correct, atol=0.1)
+        self.assertTrue(boolean_array.all())
+
+    def test_perfectnegativeslope(self):
+        W = self.linearReg.main(self.X2, self.y2)
+        boolean_array = np.isclose(W, self.W2_correct, atol=0.1)
+        self.assertTrue(boolean_array.all())
+
+    def test_multipledimension(self):
+        W = self.linearReg.main(self.X3, self.y3)
+        boolean_array = np.isclose(W, self.W3_correct, atol=0.1)
+        self.assertTrue(boolean_array.all())
+
+    def test_zeros(self):
+        W = self.linearReg.main(self.X4, self.y4)
+        boolean_array = np.isclose(W, self.W4_correct, atol=0.1)
+        self.assertTrue(boolean_array.all())
+
+    def test_noisydata(self):
+        W = self.linearReg.main(self.X5, self.y5)
+        boolean_array = np.isclose(W, self.W5_correct, atol=0.1)
+        self.assertTrue(boolean_array.all())
+
+
+if __name__ == "__main__":
+    print("Running Linear Regression Normal Equation tests:")
+    unittest.main()

ML_tests/LinearRegression_tests/LinearRegression_normal.py

@@ -0,0 +1,71 @@
+# Import folder where sorting algorithms
+import sys
+import unittest
+import numpy as np
+
+# For importing from different folders
+# OBS: This is supposed to be done with automated testing,
+# hence relative to folder we want to import from
+sys.path.append("ML/algorithms/linearregression")
+
+# If run from local:
+# sys.path.append('../../ML/algorithms/linearregression/')
+from linear_regression_normal_equation import linear_regression_normal_equation
+
+
+class TestLinearRegression_NormalEq(unittest.TestCase):
+    def setUp(self):
+        # test cases we want to run
+        self.X1 = np.array([[0, 1, 2]]).T
+        self.y1 = np.array([1, 2, 3])
+        self.W1_correct = np.array([[1, 1]])
+
+        self.X2 = np.array([[0, 1]]).T
+        self.y2 = np.array([1, 0])
+        self.W2_correct = np.array([[1, -1]])
+
+        self.X3 = np.array([[1, 2, 3], [1, 2, 4]]).T
+        self.y3 = np.array([5, 10, 18])
+        self.W3_correct = np.array([[0, 2, 3]])
+
+        self.X4 = np.array([[0, 0]]).T
+        self.y4 = np.array([0, 0])
+        self.W4_correct = np.array([[0, 0]])
+
+        self.X5 = np.array([[0, 1, 2, 3, 4, 5]]).T
+        self.y5 = np.array([0, 0.99, 2.01, 2.99, 4.01, 4.99])
+        self.W5_correct = np.array([[0, 1]])
+
+    def test_perfectpositiveslope(self):
+        W = linear_regression_normal_equation(self.X1, self.y1)
+        print(W.shape)
+        print(self.W1_correct.shape)
+        boolean_array = np.isclose(W, self.W1_correct)
+        self.assertTrue(boolean_array.all())
+
+    def test_perfectnegativeslope(self):
+        W = linear_regression_normal_equation(self.X2, self.y2)
+        boolean_array = np.isclose(W, self.W2_correct)
+        self.assertTrue(boolean_array.all())
+
+    def test_multipledimension(self):
+        W = linear_regression_normal_equation(self.X3, self.y3)
+        print(W)
+        print(self.W3_correct)
+        boolean_array = np.isclose(W, self.W3_correct)
+        self.assertTrue(boolean_array.all())
+
+    def test_zeros(self):
+        W = linear_regression_normal_equation(self.X4, self.y4)
+        boolean_array = np.isclose(W, self.W4_correct)
+        self.assertTrue(boolean_array.all())
+
+    def test_noisydata(self):
+        W = linear_regression_normal_equation(self.X5, self.y5)
+        boolean_array = np.isclose(W, self.W5_correct, atol=1e-3)
+        self.assertTrue(boolean_array.all())
+
+
+if __name__ == "__main__":
+    print("Running Linear Regression Normal Equation tests:")
+    unittest.main()