yes, the output is continuous. So I used a threshold to get binary labels.
If prediction threshold, then class is 0 else 1. I use this binary label
to then compute the accuracy. Even with this binary transformation, the
accuracy with decision tree model is low compared to LR or SVM (for the
Can you share the dataset via a gist or something and we can take a look at
what's going on?
On Fri, Jul 25, 2014 at 10:51 AM, SK skrishna...@gmail.com wrote:
yes, the output is continuous. So I used a threshold to get binary labels.
If prediction threshold, then class is 0 else 1. I use
Hi Sudha,
Have you checked if the labels are being loaded correctly? It sounds like
the DT algorithm can't find any useful splits to make, so maybe it thinks
they are all the same? Some data loading functions threshold labels to
make them binary.
Hope it helps,
Joseph
On Fri, Jul 11, 2014 at
