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)