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R/mboost.R

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@@ -426,10 +426,6 @@ mboost_fit <- function(blg, response, weights = rep(1, NROW(response)),
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cf[, which(ix)] <- cftmp
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}
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if (!is.matrix(cf)) cf <- matrix(cf, nrow = 1)
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## check if base-learner has coefficients
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if(any(sapply(cf, is.null))){
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ret <- NULL
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} else {
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ret <- switch(aggregate,
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"sum" = rowSums(cf) * nu,
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"cumsum" = {
@@ -438,7 +434,6 @@ mboost_fit <- function(blg, response, weights = rep(1, NROW(response)),
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},
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"none" = nu * cf
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)
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}
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### set names, but not for bolscw base-learner
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if (!cwlin) {
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nm <- bl[[w]]$Xnames

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