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import numpy as np | |
import pandas as pd | |
from sklearn.linear_model import LinearRegression | |
from sklearn.utils import shuffle | |
data = pd.read_csv("https://raw.githubusercontent.com/amankharwal/Website-data/master/student-mat.csv") | |
data = data[["G1", "G2", "G3", "studytime", "failures", "absences"]] | |
predict = "G3" | |
x = np.array(data.drop([predict], 1)) | |
y = np.array(data[predict]) | |
from sklearn.model_selection import train_test_split | |
xtrain, xtest, ytrain, ytest = train_test_split(x, y, test_size=0.2) | |
linear_regression = LinearRegression() | |
linear_regression.fit(xtrain, ytrain) | |
predictions = linear_regression.predict(xtest) | |
# Calculation of R2 Score | |
from sklearn.model_selection import cross_val_score | |
print(cross_val_score(linear_regression, x, y, cv=10, scoring="r2").mean()) |
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