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I'm trying to understand the result of the Odds Ratio library(nnet) model <- multinom(labs~GENDER+Education+Imp,data=mydata) GENDER = (Man, Woman) Education = (Primary, Secondary, University) Imp = (YES, NO) I have 300 participants in my study, I clustered them in 3 Clusters So in...

I'm not sure if this question is Applied Statistics, my apologies if it isn't. I have different implementations of different classification models (Discriminant Analsis, SVM, Neural Networks, Decision trees, etc) a total of 40 implementations and I need to compare them in two different sets...

In the method described here http://dmkd.cs.vt.edu/papers/TKDE17.pdf R code implementation is provided https://github.com/MLSurvival/ESP/blob/master/ESP_TKDE2016/TKDE_code.R the Kaplan-Meier estimator is initially estimated from data but then (from line 244) different distributions...