Displaying 1 result from an estimated 1 matches for "patienttrainingset".
2017 Dec 02
0
How can you find the optimal number of values to randomly sample to optimize random forest classification without trial and error?
...t_s)){
patientfreq[[i]] <-
as.data.frame(prop.table(table(factor(
patient_s[[i]], levels = 1:100
))))[,2]}
controlfreq <- t(as.data.frame(controlfreq))
controltrainingset <- transform(controlfreq, status = "control")
patientfreq <- t(as.data.frame(patientfreq))
patienttrainingset <- transform(patientfreq, status = "patient")
dataset <- rbind(controltrainingset, patienttrainingset)
This is the final data frame being used in the classification algorithm. My
goal of this post is to figure out how to identify the optimal "s" value so
that the highest...