What object types can be used for fetures in decision trees? Do I need to convert my "object" type to another type?
I used one hot encoding to convert my categorical data because the scikit-learn decision tree packages do not support categorical data.
I imported a table using pandas and I was able to set independent variables (features) and my dependent variable (target). Two of my independent variables are "object type" and my others are int64 and float64. Do I need to convert my "object" type features to "class" or another type? How can I handle these in Sci-kit learn decision trees?