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I made a classification model using the decison tree. But when i apply it, it gives me the same prediction with the same confidence level, for every example, like in this picture i posted. Can anyone tell which mistake could cause thisto happen? Thank you.
can you have alook at your tree? Could it be that it simply does not split? What happens if you deactivate pruning and prepruning in the tree?
Thank you for your answer. I will try that.
Here you can see how my process looks like, and decesion tree as well. I'm trying to do text mining but i am a beginer, so i don't know too much about it.
First i tried to run a process without connecting wordlist from the first Process Docs from Data operator to the second one, and then i've got an error message that says- atributes dont match. And then i connected those two, so now i have a problem that made me come here
According to what you show, your Decision Tree doesn't split. Wrap that DT into a Cross Validation operator and measure hte performance. My guess is that it'll classify the majority of your "0" class incorrectly.
just google for decision tree and pruning. Your tree got simply too much pruned. Most likely you need to reduce the min_gain to 0.001.