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regression python Code Example
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]]))
Source: scikit-learn.org
regression python 
# pip install polynomial-regression-model
from polynomial_regression.main import regress
dataset1 = [1, 2, 3, 4, 5]
dataset2 = [2, 3, 4, 5, 6]
regression = regress(dataset1, dataset2)



Python

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Type:
 Code Example
Category:
 Coding
Sub Category:
 Code Example
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