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[英]Different results with randomForest() and caret's randomForest (method = “rf”)
[英]Errors with createGrid for rf (randomForest) when using caret
當我嘗試創建參數網格以使用插入符號進行訓練時,出現各種錯誤:
> my_grid <- createGrid("rf")
Error in if (p <= len) { : argument is of length zero
> my_grid <- createGrid("rf", 4)
Error in if (p <= len) { : argument is of length zero
> my_grid <- createGrid("rf", len=4)
Error in if (p <= len) { : argument is of length zero
createGrid的文檔說:
This function creates a data frame that contains a grid of
complexity parameters specific methods.
Usage:
createGrid(method, len = 3, data = NULL)
Arguments:
method: a string specifying which classification model to use. See
'train' for a full list.
len: an integer specifying the number of points on the grid for
each tuning parameter.
data: the training data (only needed in the case where the 'method'
is 'cforest', 'earth', 'bagEarth', 'fda', 'bagFDA', 'rpart',
'svmRadial', 'pam', 'lars2', 'rf' or 'pls'). The outcome
should be in a column called '.outcome'.
並給出以下示例,它們可以正常工作:
createGrid("rda", 4)
createGrid("lm")
createGrid("nnet")
## data needed for SVM with RBF:
## Not run:
tmp <- iris
names(tmp)[5] <- ".outcome"
head(tmp)
createGrid("svmRadial", data = tmp, len = 4)
## End(Not run)
這樣做,我在做什么錯?
什么是之間的連接len
作為參數傳遞給createGrid
和tuneLength
在爭論train
? len
和tuneLength
可以一起使用嗎? 他們是什么關系?
如果有幫助,這里是描述如何使用一個線程createGrid
與train
在caret
: 插入記號::火車:指定型號代參數
從示例中提取的代碼對我來說很好用(並注意,它可以解決在Rhelp上發布時存在的問題):
tmp <- iris
names(tmp)[5] <- ".outcome"
head(tmp)
createGrid("svmRadial", data = tmp, len = 4)
#-------
.sigma .C
1 0.7500934 0.25
2 0.7500934 0.50
3 0.7500934 1.00
4 0.7500934 2.00
編輯:
> createGrid("rf", data = tmp, len = 4)
randomForest 4.6-7
Type rfNews() to see new features/changes/bug fixes.
Attaching package: ‘randomForest’
The following object(s) are masked from ‘package:Hmisc’:
combine
note: only 3 unique complexity parameters in default grid. Truncating the grid to 3 .
.mtry
1 2
2 3
3 4
我再說一遍:還有什么問題?
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