Hi Rin,
Can you please attach the sample data?
Two points here:
- In Automated Analytics, we do not build a decision tree - but rather derive the decision tree from the built classification or regression model. The classification or regression algorithm encodes the data in a certain way, especially for nominal values, it will group values showing similar behaviors using the KxOther category. As you can in your screenshot, the group [Apple, Google] tends to reduce the percentage of positive target.
Now if you want to predict a value for a particular company that's not Apple or Google, you would have to use the KxOther category in the "Simulating the Model" screen. BTW it's strange that the values listed there are Apple and Microsoft.
- For a more "classical" decision tree algorithm, you might want to give it a try with Expert Analytics as it provides possibilities using R algorithms. You can even compare the performance of this approach side by side with the Automated one.
Maybe it will ease the understanding if you can explain what is your use case and what you are trying to achieve.
Best regards & thanks
Antoine