I was trying to encode the string values of the feature 'ProductCategory' into integer values, but I got this error.
Also, I would like to ask if label-encoding this feature would force my model to misrepresent the integer values as 0<1<2.
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1 Answer
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LabelEncoding, if not processed again before passing into the model, will impose an order on the categories (namely the 0<1<3) that you mentioned. Here, since it does not seem like you have a lot of categories, one-hot encoding is the easiest to implement and also more effective (the categorical values are nominal rather than ordinal here).
These two articles are a decent starting point for categorical encoding in Python: https://pbpython.com/categorical-encoding.html
https://medium.com/@contactsunny/label-encoder-vs-one-hot-encoder-in-machine-learning-3fc273365621
As for the TypeError, can you double check what variable type train_df is?
