I am trying to fit a gbm model to some poisson distributed data and have run a cross validation scheme for some of gbm the parameters, including bag fraction. My results show that a bag fraction of one gives the best accuracy (in terms of poisson deviance). I have tried to read about bag fraction and understand it represents the fraction of the data used in growing the trees in subsequent iterations, meaning that my model is best when 100% of the data i used in growing the trees. I am however unsure if there are any concerns of using a bag fraction of one, and was hoping someone here could enlighten me.
Thank you in advance!