Hi all ,
I find a strange result when I try to compare the output of a model from summary()
with predict() on the same training set.
The same units are not classified in the same way, so I find two different confusion matrix.
The issue arise with trials >1 and at least 3 variables in training set.
I would expect the same results but maybe I misunderstood the inner workings of the algo.
I use
R 4.1.1
and package C50 0.1.8
This is a code that reproduce the issue from credit_data dataset:
Hi all , I find a strange result when I try to compare the output of a model from summary() with predict() on the same training set.
The same units are not classified in the same way, so I find two different confusion matrix. The issue arise with trials >1 and at least 3 variables in training set. I would expect the same results but maybe I misunderstood the inner workings of the algo.
I use R 4.1.1 and package C50 0.1.8
This is a code that reproduce the issue from credit_data dataset:
##################################################################################
confusion matrix in summary( tree_mod )
id different than confusion matrix built from predict()
##################################################################################
Thank you, Massimo