Hi everyone,

I would like to build a predictive model(Logistic regression or decision tree or NNet . But the frequency of the event I am predicting is extremely small less than 1%. In fact here is my frequency distribution of my dependent variable Churn_ind Churn_ind=1 150(0.75%) Churn_ind=0 19850(99.25%). Questions: Q1: What is the minimum sample size to run a reliable model? Q2: What model could best fit this type of distribution where my event is less than 1% and in this case 150 out of 20000 ? Q3:Is there a minimum N sample size when running a decision Tree I tried to run a decision but got no results. I turning to the group here to seek for ideas . Your assistance is more more than welcome.

Thanks,

Paul

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