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Hello, does any one know how to interpret this output in R? > Classification with logitboost > fit <- logitboost(xlearn, ylearn, xtest, presel=50, mfinal=20) > summarize(fit, ytest) Minimal mcr: 0 achieved after 6 boosting step(s) Fixed mcr: 0 achieved after 20 boosting step(s) What is "mcr" mean? Thanks [[alternative HTML version deleted]]

Hi, I am using dlda algorithm from supclust package and I am wondering if the output can be a continuous probability instead of discrete class label (zero or one) since it puts some restriction on convariance matrix, compared with lda, while the latter can. thanks, -- Weiwei Shi, Ph.D Research Scientist GeneGO, Inc. "Did you always know?" "No, I did not. But I believed..."

Hi, all, When running > AB.fit=adaboost(ylearn, xlearn, xtest, presel=0) I got the following error: Error in `[[<-.data.frame`(`*tmp*`, preds, value = c(4L, 6L, 6L, 6L, 3L, : replacement has 186 rows, data has 62 The data structure is attached below: [1] "ylearn" [1] 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 1 1...