[R] Partial dependence plot in randomForest package (all flat responses)

Hi, I'm trying to make a partial plot with package randomForest in R. After I perform my random forest object I type partialPlot(data.rforest, pred.data=act2, x.var=centroid, C) where data.rforest is my randomforest object, act2 is the original dataset, centroid is one of the predictor and C is

Re: [R] How to aggregate combinations

Thanks a lot, this is what I was looking for. All the best -- View this message in context: http://r.789695.n4.nabble.com/How-to-aggregate-combinations-tp4631867p4631980.html Sent from the R help mailing list archive at Nabble.com. __

[R] How to aggregate combinations

Hi all, Given a table like the one below, I want to get a number of vectors equal to the groups of connected ID (ID are considered connected if they are in the same row). Each vector should contains all the connected ID . e.g. In this case: vect1 (1,2,3) vect2 (5,6) vect3 (7,8,9)

Re: [R] Sampling problems

Hi, thank you but it does work for vectors and matrix but not dataframes, it gives me this message error: MeanA - read.csv(MeanAmf.csv,header=T) mysample - MeanA[sample(1:nrow(MeanA), 20, replace=FALSE),] remainder-MeanA[-mysample] Error in `[.default`(MeanA, -mysample) : invalid subscript type

Re: [R] Sampling problems

Hi sarah, it is not clear to me how to do that, can you show me please? Imagine I have a situation like this: MeanA - read.csv(MeanAmf.csv,header=T) mysample - MeanA[sample(1:nrow(MeanA), 20, replace=FALSE),] Then? -- View this message in context:

Re: [R] Sampling problems

Thanks, but it doesn't work either, it gives me the same message error. It works just if my first sample is taken in this way: mysample - sample(1:nrow(MeanA), 20, replace=FALSE) However, in this way it sample just the number of rows: [1] 71 24 12 36 2 39 69 62 43 38 9 44 13 54 50 63 67 66

[R] Simple solution

Hi everybody, Thank you all for your suggestions, you have been very helpful. However at the end I solved in this way: mysample - MaxDH[sample(1:nrow(MaxDH), 150, replace=FALSE),] A-mysample[1:120,] B-mysample[121:150,] So simple at the end... Best, Luca -- View this message in context:

[R] Sampling problems

Hi, I need to sample randomly my dataset for 1000 times. The sample need to be the 80%. I know how to do that, my problem is that not only I need the 80%, but I also need the corresponding 20% each time. Is there any way to do that? Alternatively, I was thinking to something like setdiff ()