similar to: Scaling values 0-255 -> -1 , 1 - how can this be done?

I have a dataframe that has a header like so: class value1 value2 value3 class is a factor the actual values in the columns value1, value2 and value3 are 0-255, I wish to binarize these using biclust. I can do this like so: binarize(dataframe[,-1]) this will return a dataframe, but then I lose my first column class, so I thought I could combine it like so: dataframe <-

What is the best way to produce a barplot from my data? I would like the barplot to show each person with the values stacked val1+val2+val3, so there is one bar for each person When I use barplot(data.matrix(realdata)), it shows one bar for each value instead. To post here, I created an artificical data set, but it works fine. fakedata <- as.data.frame(list(LETTERS[1:3])) colnames(fakedata)

I would like to take the values of observations and map them to a new index. I am not sure how to accomplish this. The result would look like so: x[1,2,3,4,5,6,7,8,9,10] becomes y[2,4,6,8,10,12,14,16,18,20] The "newindex" would not necessarily be this sequence, but a sequence I have stored in a vector, so it could be all kinds of values. here is what happens: > x <- rnorm(10)

I am able to split my df into two like so: dataset <- trainset index <- 1:nrow(dataset) testindex <- sample(index, trunc(length(index)*30/100)) trainset <- dataset[-testindex,] testset <- dataset[testindex,-1] So I have the index information, how could I re-combine the data using that back into a single df? I tried what I thought might work, but failed with:

I am trying to make it so two columns with similar data use the same internal numbers for same factors, here is the example: > read.csv("test.csv",header =FALSE,sep=",") V1 V2 V3 1 sun moon stars 2 stars moon sun 3 cat dog catdog 4 dog moon sun 5 bird plane superman 6 1000 dog 2000 > data <-

I am used to packages like e1071 where you have a tune step and then pass your tunings to train. It seems with caret, tuning and training are both handled by train. I am using train and trainControl to find my hyper parameters like so: MyTrainControl=trainControl( method = "cv", number=5, returnResamp = "all", classProbs = TRUE ) rbfSVM <- train(label~., data =

I have a rather basic set of data. It is simply a variable that can be 0, 1 or 2 and its value over a series of time t0 - t9 like so: y: 1 1 2 0 1 2 2 1 2 1 x: t0 t1 t2 t3 t4 t5 t6 t7 t8 t9 I need to predict what the value of y will be at t10 through t13. As you can see its rather basic. I am rather new to solving these types of problems so I am looking for some good straight forward things

I have never been able to get class probabilities to work and I am relatively new to using these tools, and I am looking for some insight as to what may be wrong. I am using caret with kernlab/ksvm. I will simplify my problem to a basic data set which produces the same problem. I have read the caret vignettes as well as documentation for ?train. I appreciate any direction you can give. I

Dear list, I think I'm being dense, but I can't get combn or expand.grid to give me this result. I need to generate a matrix of all 16 possible sequences of 4 boolean elements, 0000 0001 0010 0011 0100 ..... 1111 (in the end I'll have to assign NA to the 0s and some value to the 1s but let's keep it simple) OK, I could go the following route, but I feel like reinventing the

Hi guys, I have 1000 rows of a dataset. In my analysis, I need 70% of the data, run my analysis and then use the remaining 30% to test my model. Could anybody kindly help me on this? Cheers

I got simple x,y pairs of data and simple scatterplot and just cannot figure how to do it , there are many examples but always there is error popping out please show me an example stripped with additional data just core of what I need to do to get this damn line -- View this message in context:

I'd like to convert a dist into a table/matrix/thingy of the form: A B value A C value B C value (assuming the dist was over 3 names). Is there a way to do this without using a for loop? -- Taral <taralx at gmail.com> "Please let me know if there's any further trouble I can give you." ? ? -- Unknown

Dear R users, I am facing a pretty a unusual problem while converting character to numeric. Any input would be appreciated. Below is the code and error faced: --------------------------------------- *> str(cmie.dts)* *'data.frame': 4397 obs. of 1 variable:* * $ INE001A01036: chr "1482181740.000000" "1482181740.000000" "1482181740.000000"

Dear useRs, i have certain commands for some operations in R. They are good if you have a small dataset but my dataset, apart from what i used in the recent past, is prety large. I want to convert these massive sets of commands into a simple loop. Your help is required on it thanks in advance eliza kindly note: "e" is matrix whose each column has to be executed into a distance vector

Dear all, I share the problem Linda Garcia and Ram Kumar Basnet described; I have a biclust object, containing several clusters. For drawing a heatmap, it is possible to specify the cluster to be plotted. However, I'd like to extract the clusters in this manner: Cond.1 Cond.2 Gene - value - value just like drawHeatmap specifies each cluster. Is there a way to extract single

Dear all, I have a data frame in which the columns need to be ordered. The first column X is at the right position, but the remaining columns X1-Xn should be ordered like this: X1, X2, X3 etc instead of like below. > colnames(pos1) [1] "X" "X1" "X10" "X11" "X12" "X13" "X14" "X15" "X16"

Hi there, I'm trying to remove multiple columns by name from a data.frame. As a result I need to get back the modified data.frame without the removed columns. My columns I want to delete are listed in a vector called "delete". data <- read.csv2("data.csv") delete <- c("col1", "col2", "col3") newData <- subset(data, select =

Hi everyone, I have the following problem: I have three variables, 'group', 'city' and 'pressure' There is an interaction effect between group and city and I'd like to show this in an interaction plot: interaction.plot(group, city, pressure, type="b", col= c(1:2), leg.bty="o", leg.bg="blue", lwd=1,

Dear List, I recently started using R and I have a simple question. I am running R (v. 2.12.1) and Rcmdr (v.1-6.3) on Mac (Snow Leopard). I am using a data set I used before for practicing ANOVA with R, so I know what the results should look like. I can get ANOVA table using both Rcmdr and GUI. However, I cannot make R prepare the ANOVA diagram (with boxplots, showing the data points, including

Hi useRs, I ran into an inconsistent output problem again. Here is the simplify illustration I've got a matrix as follows > x V1 V2 V3 [1,] 1 2 3 [2,] 4 5 6 [3,] 7 8 9 Associated with the matrix is a scaling factor, sca, derived from, say the mean of the respective columns, V1-V3; > sca V1 V2 V3 2.5 1.7 3.6