Should categorical data be normalised in linear regression?

Asked Jan 31 '16 at 01:02

Active Jan 31 '16 at 01:02

Viewed 81 times

I have data similar to the following:

[
   [0, 4, 15]
   [0, 3, 7]
   [1, 5, 9]
   [2, 4, 15]
]

I used One Hot Encoder to preprocess this data so it is suitable for linear regression to give me this:

[
   [1, 0, 0, 4, 15]
   [1, 0, 0, 3, 7]
   [0, 1, 0, 5, 9]
   [0, 0, 1, 4, 15]
]

However, I then wish to normalise this data.

Should I normalise category data?

asked Jan 31 '16 at 01:02

Yahya Uddin

1

I'd simply use categorical / dummy variables. Not sure what the distance between samples on the categorical feature "axis" could mean in an Euclidean metric. – IcannotFixThis Feb 01 '16 at 07:14
2

Why do you want to normalize or standardize? – kjetil b halvorsen Jan 26 '20 at 16:36
Does this answer your question? [whether to rescale indicator / binary / dummy predictors for LASSO](https://stats.stackexchange.com/questions/69568/whether-to-rescale-indicator-binary-dummy-predictors-for-lasso) – kjetil b halvorsen Jan 26 '20 at 16:46
Please give more details of what your data are. – Peter Flom Jan 27 '20 at 11:36

0 Answers0