Displaying 5 results from an estimated 5 matches for "rfcv".
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2017 Aug 23
2
cross validation in random forest rfcv functin
Hi all,
I would like to do cross validation in random forest using rfcv function. As the documentation for this package says:
rfcv(trainx, trainy, cv.fold=5, scale="log", step=0.5, mtry=function(p) max(1, floor(sqrt(p))), recursive=FALSE, ...)
however I don't know how to build trianx and trainy for my data set, and I could not understand the way trainx...
2017 Aug 23
1
cross validation in random forest using rfcv functin
Hi all,
I would like to do cross validation in random forest using rfcv function. As the documentation for this package says:
rfcv(trainx, trainy, cv.fold=5, scale="log", step=0.5, mtry=function(p) max(1, floor(sqrt(p))), recursive=FALSE, ...)
however I don't know how to build trianx and trainy for my data set, and I could not understand the way train...
2017 Aug 23
0
cross validation in random forest using rfcv functin
Any responds?!
On Wednesday, August 23, 2017 5:50 AM, Elahe chalabi via R-help <r-help at r-project.org> wrote:
Hi all,
I would like to do cross validation in random forest using rfcv function. As the documentation for this package says:
rfcv(trainx, trainy, cv.fold=5, scale="log", step=0.5, mtry=function(p) max(1, floor(sqrt(p))), recursive=FALSE, ...)
however I don't know how to build trianx and trainy for my data set, and I could not understand the way train...
2013 Feb 13
1
context of runif()
...,
I am exploring some random forest analysis methods and have come upon one
aspect I don't fully understand from any manual. The code of interest is
as follows from the randomForest package:
myiris=cbind(iris[1:4], matrix(runif(508*nrow(iris)),nrow(iris),508))
This would be following by the rfcv() function for cross-validation but I
am confused about the former syntax.
My question is why 508? Is this some arbitrary number that one just
chooses are is there some logic to the choice? I have looked through the
package documentation and the runif() help which tells me that runif(n,
min=0, m...
2018 Mar 20
0
A new version (1.1.0) of the “spm” package for spatial predictive modelling reelased on CRAN [SEC=UNCLASSIFIED]
...a new function, tovecv, to convert relevant error measures to accuracy measure (VEcv).
3. Added some accuracy measures for categorical data and one further accuracy measure for numerical data in function pred.acc.
4. Added the variances of predictions to relevant prediction functions.
5. Revised RFcv etc. to use pred.acc.
6. Removed samples with missing values in data(hard).
6. Updated vignette accordingly.
Comments, suggestions and contributions are welcome and much appreciated!.
Kind regards,
Jin Li, PhD | Spatial Modeller / Computational Statistician
National Earth and Marine Obser...