[R] CART vs. Random Forest

[Marc R. Feldesman]

At 12:51 PM 9/25/2002, Andrew Baek wrote:
 >According to Dr. Breiman, the RF should be more accurate
 >method than a single tree. However, the performance of each
 >method seems to depend on the proprotion of outcome variable
 >in my case. My data set is a typical classification problem
 >(predict bad guys). When I ran both of them with different
 >proportion of outcome variables(there's a criterion to measure
 >the degree of bad behavior), I got very strange results.
 >
 >1. proportion of 1 to 0 = 1:4
 >err.rate of CART = 25.2%
 >err.rate of RF = 25.6%
 >
 >2. 1:9
 >err.rate of CART = 28.5%
 >err.rate of RF = 21.2%
 >
 >3. 1:33
 >err.rate of CART = 28.2%
 >err.rate of RF = 12.1%
 >
 >4. 1:99
 >err.rate of CART = 25.1%
 >err.rate of RF = 7.3%
 >
 >
 >In 3 & 4, RF looks superior to CART. But I'm afraid RF just
 >vote for "0" to reduce the error rate. Any suggestions?

Where are you getting CART results in R?  CART is a trademark of Salford 
Systems and is not implemented AFAIK in R (or SPlus).

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