Regression 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]]))

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)

Similar codes

0 vote292 views1 answer
Np minimum of array
Python
2 votes269 views1 answer
Pandas get value not equal to
Python
5 votes343 views1 answer
Flask boiler plate
Python Flask
1 vote272 views1 answer
Python second to last element in list
Python
11 votes278 views3 answers
How to pause a python script
Python
242 votes650 views6 answers
Python read text file
Python
133 votes297 views6 answers
Python read json
Python
6 votes270 views1 answer
How to get username with userid discord.py
Python
0 vote274 views1 answer
Swap two columns python
Python
2 votes295 views1 answer
Python connect sftp with key
Python