HP_model=lm.LinearRegression()for i in range(4,34,1): x=df1[col[0]].copy() y=df1[col[i]] x_train,x_test,y_train,y_test=model_selection.train_test_split(x,y,test_size=0.25) x_train=[x_train] x_test=[x_test] y_train=[y_train] y_test=[y_test] HP_model = HP_model.fit(x_train, y_train) m1=HP_model.predict(x_test) print(m1) # i copy this code from my old note book but some how it is an eror. My teacher have never seen this eror before too

Hey, Thank you for reaching out! Unfortunately, I don't have access to the df1 DataFrame and can't reproduce your results. However, such an error occurs when there is a mismatch in the dimensions of the training and testing dataset - you have trained your model on 869 features but are testing it on 290 features. Make sure that x_train and x_test have the same dimensions during all iterations. Kind regards, 365 Hristina

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Last answered:

20 Mar 2023

Posted on:

18 Mar 2023

X has 290 features, but LinearRegression is expecting 869 features as input.

in Machine Learning in Python / Course Introduction

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Hristina Hristova

Instructor

Posted on:

20 Mar 2023

X has 290 features, but LinearRegression is expecting 869 features as input.

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