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apapiu/rf_xgb.R

Last active April 29, 2016 23:01
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Random Forest of Xgboosts
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rf_xgb.R
# X is the training matrix, y are the labels.
library(xgboost)
n = 100
nrows = dim(X)[1]
nfeats = dim(X)[2]
replicate(n, {
boot_sample <- sample(1:nrows, replace = TRUE)
features_selected <- sample(1:nfeats, sqrt(nfeats)) #seems to work better for bagging
model_xgb <- xgboost(data = X[boot_sample, features_selected], label = y[boot_sample]) #choose your params here.
})
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