What is the best way to treat datetime in the preprocessing step of machine learning I have two datetime columns in my dataset. What I have done so far I have extracted year, month, dayofweek and hourofday from these columns.
So as you expect they will be something like this:
2015-5-5 08:21:20   ----&gt; 2015   5   5   8

So my question is that what is the best way to normalize these numbers. Because I think that year or other numbers will dominate my machine learning model.
I have not found any article regarding this, all explaining till this point that we convert them to year month ...
Thanks.
You already have a good beginning. Transforming data into 4 columns. Year, month, day and hour. Now These 4 are all categoricals, you can than just apply one hot Encoding. Than no Domination will happen.