Hello R users,
I'm wondering whether it is possible to manage big data set in R? I
have a data set with 3 million rows and 3 columns (X,Y,Z), where X is
the group id. For each X, I need to run 2 regression on the submatrix.
I used the function "split":
datamatrix<-read.csv("datas.csv", header=F,
Hello R users,
I'm wondering whether it is possible to manage big data set in R? I
have a data set with 3 million rows and 3 columns (X,Y,Z), where X is
the group id. For each X, I need to run 2 regression on the submatrix.
I used the function "split":
datamatrix<-read.csv("datas.csv", header=F,
Still about the mvpart.
Is there any way I can control for the number of elements in each node
in the function mvpart? Specifically, how can I ask partition to
ignore node with elements less than 10?
Thanks!
-Shu
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Hello,
I'm using the R package called mvpart, which is about the multivariate
regression trees.
The function I wrote is:
mrt1<- mvpart(coefmat~sChip+sScreen+sMem,data=mixdata, xv="pick",
plot.add=TRUE,uniform=TRUE,which=4,all=TRUE,xadj=2,yadj=2,rsq=TRUE,big.pts=TRUE,wgt.ave.pca=TRUE,legend=TRUE,ba
Hello,
I'm using the R package called mvpart, which is about the multivariate
regression trees.
The function I wrote is:
mrt1<- mvpart(coefmat~sChip+sScreen+sMem,data=mixdata, xv="pick",
plot.add=TRUE,uniform=TRUE,which=4,all=TRUE,xadj=2,yadj=2,rsq=TRUE,big.pts=TRUE,wgt.ave.pca=TRUE,legend=TRUE,b
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