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 vote273 views1 answer
/bin/sh: 1: python: not found
Python
46 votes261 views6 answers
Dataframe to CSV
Python
0 vote270 views1 answer
Print python setencode
Python
23 votes293 views5 answers
Pandas select rows by multiple conditions
Python
4 votes263 views3 answers
Unable to locate package python-pip
Python
4 votes287 views3 answers
Python create 2d array deep copy
Python
-1 vote258 views1 answer
Python graphql client
Python
2 votes263 views1 answer
Drop column
Python
1 vote262 views1 answer
Python moving average of list
Python
19 votes273 views6 answers
Python tkinter window size
Python