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Predicting house prices using Linear Regression and GBR
I think scaling should be considered before performing linear regression.
Hi one suggestion I have I can try to use streamlit to create a nice UI for this with sliders and also to predict the data.
In your code at In [29], near the bottom gives this error: NameError: name 'params' is not defined.
Then the rest of the code will not execute without that defined previously.
Hi Shreyas
I need to know that in this data what 'grade' and 'condition' values stands for like what info thus these number in these column provide.
If you want to apply scaling techniques on they should be applied before model building. Also while applying make sure you fit_transform on Train and transform on the Test.
In the model from sklearn.cross_validation import train_test_split
should be from sklearn.model_selection import train_test_split
as the module name is changed if we don't do that it will through an error.
Hope this will help others.
Cheers.
the variable (or some deprecated part of sklearn) named 'params' has been used here.
which raises the error name 'params' is not defined
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