Training Linear Regression Model on 85% of Dataset

Question

I'm not exactly sure how to approach this question. The dataset has 8 attributes and one y-value. How would I train a linear regression model on 85% of the dataset?

Answer 1

You can also use train_test_split from sklearn as in sklearn example to split the data into training and testing sets e.g. if X is data with features and y is label then:

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.15)

And for linear regression you can try using: linregress from scipy as in similar question:

Answer 2

Use ndf = df.sample(frac=0.85) to get a DataFrame with 85% of your total rows and then use this new DataFrame ndf to train your linear regression model.