similar to: confusion() -- generic function in package mda -- generally useful?

Dear R users, I have a question on the confusion matrix generated by function randomForest. I used the entire data set to generate the forest, for example: > print(iris.rf) Call: randomForest(formula = Species ~ ., data = iris, importance = TRUE, keep.forest = TRUE) confusion setosa versicolor virginica class.error setosa 50 0 0 0.00

On 28/10/2017 7:12 AM, Morkus wrote: > Thanks Duncan. Awesome ideas! > > I think we're getting closer! > > I tried what you suggested and got a possibly better error... > . > . > . > rConnection.assign("boxMVariable", myDf); > > *String resultBV *= *"str(boxMVariable)"*; *// your suggestion.* > > *RESULTING ERROR:* > >

Hello, I have noticed a bug with LSSVM implementation in R. It could be a bug with the LSSVM itself that causes this problem. I thought I should post this message to see if anyone else is familiar with this problem and explain why the result is different for odd and even number of cases. Once the hyperplane is found using LSSVM, the prediction results vary when you predict odd or even number of

On 28/10/2017 8:59 AM, Morkus wrote: > Hey Duncan, > > Hard to debug? That's an understatement. Eyes bleeding.... > > In any case, I tried all your suggestions. To get "integer" for the > final column, I had to change the code to get integers instead of strings. The last column in iris is actually a factor. That's stored as an S3-classed integer vector

On 29/10/2017 7:26 AM, Morkus wrote: > Thanks Duncan. I can't tell you how helpful all your terrific replies > have been. > > I think the biggest surprise is that nobody appears to be using Java and > R together like I"m trying to do. I suppose it should be a surprise > since there are no books on the subject and almost no technical > documentation other than a

Thanks Duncan. Awesome ideas! I think we're getting closer! I tried what you suggested and got a possibly better error... . . . rConnection.assign("boxMVariable", myDf); String resultBV = "str(boxMVariable)"; // your suggestion. RESULTING ERROR: Error in format.default(nam.ob, width = max(ncn), justify = "left") : invalid 'width' argument (No idea

Thanks Duncan. I can't tell you how helpful all your terrific replies have been. I think the biggest surprise is that nobody appears to be using Java and R together like I"m trying to do. I suppose it should be a surprise since there are no books on the subject and almost no technical documentation other than a few sites here and there. ----- I originally had the "int" as the

Hey Duncan, Hard to debug? That's an understatement. Eyes bleeding.... In any case, I tried all your suggestions. To get "integer" for the final column, I had to change the code to get integers instead of strings. double[] d1 = ((REXPVector) ((RList) tableRead).get(0)).asDoubles(); double[] d2 = ((REXPVector) ((RList) tableRead).get(1)).asDoubles(); double[] d3 = ((REXPVector)

Just print the string you are asking to R to evaluate. It doesn't make any sense as an R expression. Fix that, and things will work. Duncan Murdoch On 27/10/2017 3:41 PM, Morkus via R-devel wrote: > It can't be this hard, right? I really need a shove in the right direction here. Been spinning wheels for three days. Cannot get past the errors. > > I'm doing something

Does it work if you supply the closing parenthesis on the call to boxM? The parser says the input is incomplete and a missing closing parenthesis would cause that error.. // create a string command with that variable name.String boxVariable = "boxM(boxMVariable [,-5], boxMVariable[,5]"; // try to execute the command... // FAILS with org.rosuda.REngine.Rserve.RserveException: eval

Renjin is not R.?? Renjin is an R language interpreter written in Java. It has become exceedingly obvious that you are making user errors.??That's not a bug in the language. If you want to use Renjin, there are mailing lists devoted to Renjin, and also Stack Overflow and Renjin list questions that cover exactly what you've asked about (loading packages in Renjin when Renjin is used as a

On 28/10/2017 6:26 AM, Morkus wrote: > I'm not sure what you mean. Could you please be more specific? You were trying to eval an expression that you constructed in Java. I was suggesting that before you eval it, you print it. > > If I print the string, I get: *boxM(boxMVariable[, -5], boxMVariable[, 5])* Right, that's what I was suggesting you do. Now you've fixed the

Just out of curiosity, I took the default "iris" example in the RF helpfile... but seeing the admonition against using the formula interface for large data sets, I wanted to play around a bit to see how the various options affected the output. Found something interesting I couldn't find documentation for... Just like the example... > set.seed(12) # to be sure I have

Hi All, OK, in the "back to the drawing board" department, I found what looks like a much better solution to using R in Java. Renjin. Looking at the docs and then trying a quick example, didn't quite work. Of course I'm missing something. Although I'm telling the engine to require ("biotools") just like I would in R itself, when I get to the line of code that

I'm not sure what you mean. Could you please be more specific? If I print the string, I get: boxM(boxMVariable[, -5], boxMVariable[, 5]) From this code: . . . // assign the data to a variable.rConnection.assign("boxMVariable", myDf); // create a string command with that variable name.String boxVariable = "boxM(boxMVariable[, -5], boxMVariable[, 5])";

It can't be this hard, right? I really need a shove in the right direction here. Been spinning wheels for three days. Cannot get past the errors. I'm doing something wrong, obviously, since I can easily compute the Box's M right there in RStudio But I don't see what is wrong below with the coding equivalent. The entire code snippet is below. The code fails below on the call to

I have a question on the output generated by randomForest in classification mode, specifically, the confusion matrix. The confusion matrix lists the various classes and how the forest classified each one, plus the classification error. Are these numbers essentially averages over all the trees in the forest? If so, is there a way I can get the standard deviation values out of the randomForest,

If do: > library("e1071") > example(svm) I get: svm> data(iris) svm> attach(iris) svm> ## classification mode svm> # default with factor response: svm> model <- svm(Species ~ ., data = iris) svm> # alternatively the traditional interface: svm> x <- subset(iris, select = -Species) svm> y <- Species svm> model <- svm(x, y) svm>

Hi there: I have a question about generating mean value of a data.frame. Take iris data for example, if I have a data.frame looking like the following: --------------------- Sepal.Length Sepal.Width Petal.Length Petal.Width Species 1 5.1 3.5 1.4 0.2 setosa 2 4.9 3.0 1.4 0.2

On Fri, Mar 23, 2018 at 6:43 PM, Rui Barradas <ruipbarradas at sapo.pt> wrote: > Hello, > > Not exactly an answer but here it goes. > If you use the formula interface the names will be retained. Also if you pass named arguments: aggregate(iris["Sepal.Length"], by = iris["Species"], FUN = foo) # Species Sepal.Length # 1 setosa 5.006 # 2