airbnb_21

airbnb_21.py

from sklearn import linear_model
from sklearn.model_selection import train_test_split
X_train, X_test, Y_train, Y_test = train_test_split(X_2, y,test_size = 0.25, random_state = 0)
# Create linear regression object
regr = linear_model.LinearRegression(fit_intercept=True) # Do not use fit_intercept = False if you have removed 1 column after dummy encoding
# Train the model using the training sets
regr.fit(X_train, Y_train)
y_pred = regr.predict(X_test)

#Checking between observed and predicted data
df = pd.DataFrame({'Actual': Y_test.values.flatten(), 'Predicted': y_pred.flatten()})
df.head(25)