PYTHON

scikit learn linear regression

from sklearn.linear_model import LinearRegression
X = np.array([[1, 1], [1, 2], [2, 2], [2, 3]])
y = np.dot(X, np.array([1, 2])) + 3
reg = LinearRegression().fit(X, y)
reg.score(X, y)
reg.coef_
reg.intercept_
reg.predict(np.array([[3, 5]]))

scikit learn linear regression

from sklearn.linear_model import LinearRegression
reg = LinearRegression()
reg.score(X, y) #Fit linear model
reg.coef_ #Estimated coefficients for the linear regression problem
reg.predict(y) #Predict using the linear model