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CALSCALE:GREGORIAN
BEGIN:VEVENT
UID:5f6fc854-aaff-410f-a967-395eff7809c9@nexttoyou
DTSTAMP:20261105T160430Z
DTSTART:20261105T190000Z
DTEND:20261105T210000Z
SUMMARY:Introduction to Random Forests
DESCRIPTION:This workshop is designed as an extension to our Introduction 
 to Classification and Regression Trees workshop. Making inference from a 
 single tree analysis may be severely limited by over-fitting to the datas
 et at hand. Minor changes to the data can greatly change the tree structu
 re and model inference. In addition\, the recursive partitioning method u
 sed in constructing a tree is a “greedy” algorithm\, meaning that the bes
 t split at the beginning of the analysis does not always result in the be
 st tree to characterize the entire data set.\n\nA random forest analysis 
 involves creating many trees and combining the results. This process redu
 ces the variance of resulting model predictions through bagging (repeated
 ly sampling the training data) and decorrelating the trees (randomly subs
 etting the set of predictors at each split). This workshop will cover the
  motivation for using random forests\, details on how they are assembled\
 , and how to build and assess random forests in R.\n\nRegister Now\n\nhtt
 p://next-to-u.app/events/5f6fc854-aaff-410f-a967-395eff7809c9
URL:http://next-to-u.app/events/5f6fc854-aaff-410f-a967-395eff7809c9
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