replace nround with nrounds to match actual parameter (#3592)
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Philip Hyunsu Cho
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@@ -222,7 +222,7 @@ The code below is very usual. For more information, you can look at the document
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```r
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bst <- xgboost(data = sparse_matrix, label = output_vector, max.depth = 4,
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eta = 1, nthread = 2, nround = 10,objective = "binary:logistic")
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eta = 1, nthread = 2, nrounds = 10,objective = "binary:logistic")
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```
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```
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@@ -244,7 +244,7 @@ A model which fits too well may [overfit](http://en.wikipedia.org/wiki/Overfitti
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> Here you can see the numbers decrease until line 7 and then increase.
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>
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> It probably means we are overfitting. To fix that I should reduce the number of rounds to `nround = 4`. I will let things like that because I don't really care for the purpose of this example :-)
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> It probably means we are overfitting. To fix that I should reduce the number of rounds to `nrounds = 4`. I will let things like that because I don't really care for the purpose of this example :-)
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Feature importance
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------------------
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@@ -448,7 +448,7 @@ train <- agaricus.train
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test <- agaricus.test
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#Random Forest™ - 1000 trees
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bst <- xgboost(data = train$data, label = train$label, max.depth = 4, num_parallel_tree = 1000, subsample = 0.5, colsample_bytree =0.5, nround = 1, objective = "binary:logistic")
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bst <- xgboost(data = train$data, label = train$label, max.depth = 4, num_parallel_tree = 1000, subsample = 0.5, colsample_bytree =0.5, nrounds = 1, objective = "binary:logistic")
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```
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```
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@@ -457,7 +457,7 @@ bst <- xgboost(data = train$data, label = train$label, max.depth = 4, num_parall
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```r
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#Boosting - 3 rounds
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bst <- xgboost(data = train$data, label = train$label, max.depth = 4, nround = 3, objective = "binary:logistic")
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bst <- xgboost(data = train$data, label = train$label, max.depth = 4, nrounds = 3, objective = "binary:logistic")
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```
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```
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