build decision tree paths with categorical data (Without Encoding)
Budget: $250 – $750 USD
I need to build decision tree decision paths with some categorical and some continuous data.
I prefer python (pandas in particular as much as possible) however, i have attempted this numerous ways and cant find a solution in that langauge. Model was initially built in SAS.
Sample provided (Tree Table)
NB = number of data points that went to that path
Percent, the percent of the data that ended up at that node
Percent good - the percent of that that was good
Percent Bad - percent that was bad
parent node -
split value - feature node was split on
split value - the value where split occurred
I prefer python (pandas in particular as much as possible) however, i have attempted this numerous ways and cant find a solution in that langauge. Model was initially built in SAS.
Sample provided (Tree Table)
NB = number of data points that went to that path
Percent, the percent of the data that ended up at that node
Percent good - the percent of that that was good
Percent Bad - percent that was bad
parent node -
split value - feature node was split on
split value - the value where split occurred