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fix matrix form prediction

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unknown 2015-03-28 23:03:16 -07:00
parent b04591cbfc
commit 930497e271
1 changed files with 16 additions and 2 deletions
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18
R-package/R/xgb.cv.R
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@ -95,7 +95,18 @@ xgb.cv <- function(params=list(), data, nrounds, nfold, label = NULL, missing =
}
folds <- xgb.cv.mknfold(dtrain, nfold, params)
predictValues <- rep(0,xgb.numrow(dtrain))
obj_type = params[['objective']]
mat_pred = FALSE
if (!is.null(obj_type) && obj_type=='multi:softprob')
{
num_class = params[['num_class']]
if (is.null(num_class))
stop('must set num_class to use softmax')
predictValues <- matrix(0,xgb.numrow(dtrain),num_class)
mat_pred = TRUE
}
else
predictValues <- rep(0,xgb.numrow(dtrain))
history <- c()
for (i in 1:nrounds) {
msg <- list()
@ -106,7 +117,10 @@ xgb.cv <- function(params=list(), data, nrounds, nfold, label = NULL, missing =
msg[[k]] <- xgb.iter.eval(fd$booster, fd$watchlist, i - 1, feval) %>% str_split("\t") %>% .[[1]]
} else {
res <- xgb.iter.eval(fd$booster, fd$watchlist, i - 1, feval, prediction)
predictValues[fd$index] <- res[[2]]
if (mat_pred)
predictValues[fd$index,] <- res[[2]]
else
predictValues[fd$index] <- res[[2]]
msg[[k]] <- res[[1]] %>% str_split("\t") %>% .[[1]]
}
}