def test_MyLinearRegressing():
x = np.array([[12.4956442], [21.5007972], [
31.5527382], [48.9145838], [57.5088733]])
y = np.array([[37.4013816], [36.1473236], [
45.7655287], [46.6793434], [59.5585554]])
lr1 = MyLR([2, 0.7])
# Example 0.0:
print(lr1.predict_(x), end="\n\n")
# Output:
# array([[10.74695094],
# [17.05055804],
# [24.08691674],
# [36.24020866],
# [42.25621131]])
# Example 0.1:
print(lr1.cost_elem_(lr1.predict_(x), y), end="\n\n")
# Output:
# array([[77.72116511],
# [49.33699664],
# [72.38621816],
# [37.29223426],
# [78.28360514]])
# Example 0.2:
print(lr1.cost_(lr1.predict_(x), y), end="\n\n")
# Output:
# 315.0202193084312
# Example 1.0:
# lr2 = MyLR([0, 0])
lr2 = MyLR([1, 1], 5e-8, 1500000)
lr2.fit_(x, y)
print(lr2.thetas, end="\n\n")
# Output:
# array([[1.40709365],
# [1.1150909]])
# Example 1.1:
print(lr2.predict_(x), end="\n\n")
# Output:
# array([[15.3408728],
# [25.38243697],
# [36.59126492],
# [55.95130097],
# [65.53471499]])
# Example 1.2:
print(lr2.cost_elem_(lr2.predict_(x), y), end="\n\n")
# Output:
# array([[35.6749755],
# [4.14286023],
# [1.26440585],
# [29.30443042],
# [22.27765992]])
# Example 1.3:
print(lr2.cost_(lr2.predict_(x), y), end="\n\n")
lr1 = MyLR([2, 0.7])
# Example 0.0:
print("Example 0.0")
print(lr1.predict_(x))
# Output:
# array([[10.74695094],
# [17.05055804],
# [24.08691674],
# [36.24020866],
# [42.25621131]])
# Example 0.1:
print("\nExample 0.1")
print(lr1.cost_elem_(lr1.predict_(x), y))
# Output:
# array([[77.72116511],
# [49.33699664],
# [72.38621816],
# [37.29223426],
# [78.28360514]])
# Example 0.2:
print("\nExample 0.2")
print(lr1.cost_(lr1.predict_(x), y))
# Output:
# 315.0202193084312
# Example 1.0:
lr2 = MyLR([1, 1], 5e-8, 1500000)
import numpy as np
from my_linear_regression import MyLinearRegression as MyLR
if __name__ == "__main__":
X = np.array([[1., 1., 2., 3.], [5., 8., 13., 21.], [34., 55., 89., 144.]])
Y = np.array([[23.], [48.], [218.]])
mylr = MyLR([[1.], [1.], [1.], [1.], [1]])
print("# Example 0:")
print(mylr.predict(X))
print("# Output:")
print("array([[8.], [48.], [323.]])")
print()
print("# Example 1:")
print(mylr.cost_elem_(X,Y))
print("# Output:")
print("array([[37.5], [0.], [1837.5]])")
print()
print("# Example 2:")
print(mylr.cost_(X,Y))
print("# Output:")
print(1875.0)
print()
# sys.lol()
print("# Example 3:")
mylr.fit_(X, Y)
print(mylr.theta)
print("# Output:")