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Oppiskele Challenge | Multiple Linear Regression
Linear Regression for ML

bookChallenge

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).

1234
import 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())
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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.

Tehtävä

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  1. Assign the 'age' and 'square_feet' columns of df to X.
  2. Build and train the model using the LinearRegression class.
  3. Predict the target for X_new.

Ratkaisu

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Osio 2. Luku 4
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Completion rate improved to 5.56

bookChallenge

Pyyhkäise näyttääksesi valikon

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).

1234
import 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())
copy

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.

Tehtävä

Swipe to start coding

  1. Assign the 'age' and 'square_feet' columns of df to X.
  2. Build and train the model using the LinearRegression class.
  3. Predict the target for X_new.

Ratkaisu

Switch to desktopVaihda työpöytään todellista harjoitusta vartenJatka siitä, missä olet käyttämällä jotakin alla olevista vaihtoehdoista
Oliko kaikki selvää?

Miten voimme parantaa sitä?

Kiitos palautteestasi!

close

Awesome!

Completion rate improved to 5.56
Osio 2. Luku 4
single

single

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