Challenge
For this challenge, the same housing dataset will be used.
However, now it has two features: age and area of the house (columns age and square_feet).
1234import pandas as pd df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/b22d1166-efda-45e8-979e-6c3ecfc566fc/houseprices.csv') print(df.head())
Your task is to build a Multiple Linear Regression model using the OLS class. Also, you will print the summary table to look at the p-values of each feature.
Swipe to start coding
- Assign the
'age'and'square_feet'columns ofdftoX. - Build and train the model using the
LinearRegressionclass. - Predict the target for
X_new.
Solution
Merci pour vos commentaires !
single
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For this challenge, the same housing dataset will be used.
However, now it has two features: age and area of the house (columns age and square_feet).
1234import pandas as pd df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/b22d1166-efda-45e8-979e-6c3ecfc566fc/houseprices.csv') print(df.head())
Your task is to build a Multiple Linear Regression model using the OLS class. Also, you will print the summary table to look at the p-values of each feature.
Swipe to start coding
- Assign the
'age'and'square_feet'columns ofdftoX. - Build and train the model using the
LinearRegressionclass. - Predict the target for
X_new.
Solution
Passez à un bureau pour une pratique réelleContinuez d'où vous êtes en utilisant l'une des options ci-dessousMerci pour vos commentaires !
single
