Jul-04-2022, 04:48 AM
# Import statements
from sklearn.linear_model import LinearRegression
from sklearn.model_selection import train_test_split
from sklearn.metrics import r2_score
import pandas as pd
# Read the data.
data = pd.read_csv('data.csv')
# Assign the features to the variable X, and the labels to the variable Y.
X = data['YearsExperience']
Y = data['Salary']
X_train,X_test,Y_train,Y_test = train_test_split(X,Y, test_size=0.33)
model = LinearRegression()
# TODO: Fit the model.
model.fit(X_train,Y_train)
# TODO: Make predictions. Store them in the variable y_pred.
y_pred = model.predict(X_test)
# TODO: Calculate the accuracy and assign it to the variable acc.
r2_score = r2_score(Y_test,y_pred)
print(r2_score)
