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I've been working on a house price prediction. After I've used standardscaler and gridsearch, the error turns out to be -66031776763.3788. Below is the code and the dataset. Could anyone tell me what is wrong with my code?

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desertnaut
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James Xu
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    Welcome to SO. Please post your code inline and not as images. – petezurich Aug 01 '18 at 06:06
  • In the line `x_train = pd.concat(frames...)` you are only selecting 5 columns (`'sqft_living', 'grade', 'sqft_above', 'sqft_living15', 'bathrooms'`). Why not use other columns? – Vivek Kumar Aug 01 '18 at 13:46

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Why you think there is some problem? Looks like you run the grid search and select the best model, with MSE = 66031776763. (You use negative of this error as score which you try to maximize, so thats why your number is negative). So the RMSE is about 256966. Given that that you are predicting price, which is usually between 200k - 1M (as i can see from your data), the error seems to be feasible. It means that linear SVM which you used is not so good (RMSE 250k is relatively large), but is's not anything out of reality.

Jakub Koubele
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