linear regression sklearn

Testy Toucan answered on September 6, 2020 Popularity 10/10 Helpfulness 3/10

answer linear regression sklearn

related scikit learn linear regression

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linear regression sklearn

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import numpy as np
from sklearn.linear_model import LinearRegression
X = np.array([[1, 1], [1, 2], [2, 2], [2, 3]])
# y = 1 * x_0 + 2 * x_1 + 3
y = np.dot(X, np.array([1, 2])) + 3
reg = LinearRegression().fit(X, y)
reg.score(X, y)
1.0
reg.coef_
array([1., 2.])
reg.intercept_
3.0...
reg.predict(np.array([[3, 5]]))

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Contributed on May 29 2023

Testy Toucan

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scikit learn linear regression

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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]]))

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Source: scikit-learn.org

Tags: linear-regression linear-regressio

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Contributed on Sep 06 2020

Zany Zebra

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scikit learn linear regression

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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

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Contributed on May 07 2021

Roscoe

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linear regression using sklearn

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df = pd.read_csv('bottle.csv')
print(df)
df_binary = df[['Salnty', 'T_degC']]
print(df_binary)
  
# Taking only the selected two attributes from the dataset
df_binary.columns = ['Sal', 'Temp']
#display the first 5 rows
df_binary.head()

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Tags: linear-regression linear-regressio

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Contributed on Feb 26 2023

Hafizuddin Syed

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linear regression sklearn

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