search for: n_l

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2011 Jun 13
1
In rpart, how is "improve" calculated? (in the "class" case)
....38 ? # Here is what I thought it should have been: # for "information" entropy <- function(p) { if(any(p==1)) return(0) # works for the case when y has only 0 and 1 categories... -sum(p*log(p,2)) } gini <- function(p) {sum(p*(1-p))} obs_1 <- y[x>.5] obs_0 <- y[x<.5] n_l <- sum(x>.5) n_R <- sum(x<.5) n <- length(x) # for entropy (information) impurity_root <- entropy(prop.table(table(y))) impurity_l <- entropy(prop.table(table(obs_0))) impurity_R <-entropy(prop.table(table(obs_1))) # shouldn't this have been "improve" ?? impur...
2011 Jun 21
0
How does rpart computes "improve" for split="information"?? (which seems to be different then the "gini" case)
...help with explaining it? Bellow is some R code simply showing how the gini is computed (and how the information is not as clear) # creating data set.seed(1324) y <- sample(c(0,1), 20, T) x <- y x[1:5] <- 0 # manually making the first split obs_L <- y[x<.5] obs_R <- y[x>.5] n_L <- sum(x<.5) n_R <- sum(x>.5) n <- length(x) calc.impurity <- function(func = gini) { impurity_root <- func(prop.table(table(y))) impurity_L <- func(prop.table(table(obs_L))) impurity_R <-func(prop.table(table(obs_R))) imp <- impurity_root - ((n_L/n)*impurity_l + (n...
2009 Jul 23
1
[PATCH server] changes required for fedora rawhide inclusion.
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