import np as np
import sklearn.linear_model as sk
import numpy as np
import matplotlib.pyplot as plt
y = np.array([1, 1, 1, 1, 1, 2, 2, 2, 2, 2])
x = np.array([[1], [2], [3], [7], [5], [27], [28], [22], [50], [70]])
p = np.array([[-3], [40]])
model = sk.LinearRegression()
model.fit(x, y)
print(model.predict(p))

46f465f7cd6feba7db81a733241e42a6ae0f7101
<mask token>

<mask token>
model.fit(x, y)
print(model.predict(p))

<mask token>
y = np.array([1, 1, 1, 1, 1, 2, 2, 2, 2, 2])
x = np.array([[1], [2], [3], [7], [5], [27], [28], [22], [50], [70]])
p = np.array([[-3], [40]])
model = sk.LinearRegression()
model.fit(x, y)
print(model.predict(p))

import np as np
import sklearn.linear_model as sk
import numpy as np
import matplotlib.pyplot as plt
y = np.array([1, 1, 1, 1, 1, 2, 2, 2, 2, 2])
x = np.array([[1], [2], [3], [7], [5], [27], [28], [22], [50], [70]])
p = np.array([[-3], [40]])
model = sk.LinearRegression()
model.fit(x, y)
print(model.predict(p))
