python - What does the value of 'leaf' in the following xgboost model tree diagram means?

Question

I am guessing that it is conditional probability given that the above (tree branch) condition exists. However, I am not clear on it.

If you want to read more about the data used or how do we get this diagram then go to : http://machinelearningmastery.com/visualize-gradient-boosting-decision-trees-xgboost-python/

Answer 1

For a classification tree with 2 classes {0,1}, the value of the leaf node represent the raw score for class 1. It can be converted to a probability score by using the logistic function. The calculation below use the left most leaf as an example.

1/(1+np.exp(-1*0.167528))=0.5417843204057448

What this means is if a data point ends up being distributed to this leaf, the probability of this data point being class 1 is 0.5417843204057448.