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Calcite | Level 5


I am building a predictive model using a decision tree, the target is binary (5.8% of the population) and there are both numeric and nominal explanatory variables. Once i build the model using the automatic mode i find that the result is blank i.e there is only the root node. I then tried building an interactive decision tree and found that the model was not able to predict many leavers.

Has anybody come across a blank decision tree and does this imply something wrong with a setting/input data etc



Obsidian | Level 7

There are many reasons why that could be happening. In theory, your explanatory variables might not have enough power to generte a split. I very much doubt that is the case. If you provide more details it might be easier for us to help. Usually this comes down to a combination of factors. For example, if your sample is too small, and you try to predict a rare event, and you also set a minimum leaf size too high, the tree might not be able to find a split that satisfies purity and minimum leaf size at the same time.


Calcite | Level 5

thanks so much for the response, you were absolutely right about the settings, once changed the tree began to blossom.....

Very much appreciated, saved me a lot of time


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