H2O 中的热编码数据会以某种方式影响 model 吗？

Question

I have hot encoded data separately (there are multiple categories under a single main variable and 30 variables). I want to know if this will effect GB, GL, DRF in H2O. the documentation says for XGBOOST it internally encodes to one-hot For deep learning models i can may be use All factor parameter but I cannot find how to stop implicit hot encoding or let it be as the results will be same?

I have read documentation and tutorial published by amazonaws, may be I am missing something.

Answer 1

If you have categorical columns, you don't need to encode it. You just need to make sure that that column is read in as enum and not int. For Deeplearning, if you want to use all factors of the categorical columns, you just need to set the parameter use_all_factor_levels=True/true/TRUE for Python, Java or R.