search for: testsets

Dear Sir, I got a problem with my program. I would like to classify my data using bagging support vector machine ensemble. I split my data into training data and test data. For a given data sets TR(X), K replicated training data sets are first randomly generated by bootstrapping technique with replacement. Next, Support Vector Mechine (SVM) is applied for each bootstrap data sets. Finally, the

COnsider the following: Age<-c(48, 57, 56, 76, 76, 66, 70, 14, 7, 3, 62, 62, 30, 10, 7, 53, 44, 29, 46, 47, 15, 13, 84, 77, 26) SerialNo<-c(001147, 005979, 005979, 006128, 006128, 007004, 007004, 007004, 007004, 007004, 007438, 007438,009402,009402, 009402, 012693, 012693, 012693, 014063,014063, 014063, 014063, 014811, 014811,016570) TestSet<-cbind(Age,SerialNo)

Hi, I am trying to construct a svmpoly model using the "caret" package (please see code below). Using the same data, without changing any setting, I am just changing the seed value. Sometimes it constructs the model successfully, and sometimes I get an ?Error in indexes[[j]] : subscript out of bounds?. For example when I set seed to 357 following code produced result only for 8

I am new to R, so I am sure I am making a simple mistake. I am including complete information in hopes someone can help me. Basically my data in R looks good, I write it to a file, and every value is off by 1. Here is my flow: > str(prediction) Factor w/ 10 levels "0","1","2","3",..: 3 1 10 10 4 8 1 4 1 4 ... - attr(*, "names")= chr

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:

Hi Karthik, Thank you very much, you made me much more relaxed. Below is getfattr output for a file from all the bricks: root at gv2 ~ # getfattr -d -e hex -m . /data/glusterfs/testset/306/30677af808ad578916f54783904e6342.pack getfattr: Removing leading '/' from absolute path names # file: data/glusterfs/testset/306/30677af808ad578916f54783904e6342.pack

Hi, has anyonne experienced problems between the LaTeX beamer class and Sweave? The following code does not work properly: ################################# \documentclass{beamer} \usepackage[latin1]{inputenc} \usepackage[T1]{fontenc} \usepackage{ngerman} \begin{document} \frame{ \frametitle{test} test <<>>= 1+1 @ } \end{document} ################################# Below is the

Hi Karthik, Thank you for your reply. The heal is still undergoing, as the /var/log/glusterfs/glustershd.log keeps growing, and there's a lot of pending entries in the heal info. The gluster version is 3.10.9 and 3.10.10 (the version update in progress). It doesn't have info summary [yet?], and the heal info is way too long to attach here. (It takes more than 20 minutes just to collect

Hello, I am using e1071 to run support vector machine. I would like to plot the data with lattice and specifically show the hyperplanes created by the system. I can store the hyperplane as a contour in an object, and I can plot one object at a time. Since there will be thousands of elements to plot, I can't manually add them one by one to the plot, so I tried to loop into them, but only the

Forgive the newbie question, I want to select random rows from my data.frame to create a test set (which I can do) but then I want to create a training set using whats left over. Example code: acc <- read.table("accOUT.txt", header=T, sep = ",", row.names=1) #select 400 random rows in data training <- acc[sample(1:nrow(acc), 400, replace=TRUE),] #try to get whats left

Hi, I have a database of 2211 rows with 31 entries each and I manually split my data into 10 folds for cross validation. I build logistic regression model as: >model <- glm(qual ~ AgGr + FaHx + PrHx + PrSr + PaLp + SvD + IndExam + Rad +BrDn + BRDS + PrinFin+ SkRtr + NpRtr + SkThck +TrThkc + SkLes + AxAdnp + ArcDst + MaDen + CaDt + MaMG + MaMrp + MaSh +

Hi everyone I am trying to do cross validation (10 fold CV) by using e1071:svm method. I know that there is an option (?cross?) for cross validation but still I wanted to make a function to Generate cross-validation indices using pls: cvsegments method. ##################################################################### Code (at the end) Is working fine but sometime caret:confusionMatrix

All, I'm trying again with a slightly more generic version of my first question. I can extract the plotted values from hist(), boxplot(), and even plot.randomForest(). Observe: # get some data dat <- rnorm(100) # grab histogram data hdat <- hist(dat) hdat #provides details of the hist output #grab boxplot data bdat <- boxplot(dat) bdat #provides details of the boxplot

Hello, I am running SVM and showing the results with ggplot2. The results include the decision boundaries, which are two dashed lines parallel to a solid line. I would like to remove the dashed lines and use a shaded area instead. How can I do that? Here is the code I wrote.. ``` library(e1071) library(ggplot2) set.seed(100) x1 = rnorm(100, mean = 0.2, sd = 0.1) y1 = rnorm(100, mean = 0.7, sd =

Hi folks, I'm troubled moving an arbiter brick to another server because of I/O load issues. My setup is as follows: # gluster volume info Volume Name: myvol Type: Distributed-Replicate Volume ID: 43ba517a-ac09-461e-99da-a197759a7dc8 Status: Started Snapshot Count: 0 Number of Bricks: 3 x (2 + 1) = 9 Transport-type: tcp Bricks: Brick1: gv0:/data/glusterfs Brick2: gv1:/data/glusterfs Brick3:

On Tue, Oct 27, 2020 at 6:04 PM Luigi Marongiu <marongiu.luigi at gmail.com> wrote: > > Hello, > I am using e1071 to run support vector machine. I would like to plot > the data with lattice and specifically show the hyperplanes created by > the system. > I can store the hyperplane as a contour in an object, and I can plot > one object at a time. Since there will be

Dear all, I am trying to do a n-fold cross-validation for a regularized discrimant function analysis using rda from the package klaR. However, I have problems to predict the groups from the test/validation sample. The exmaples of the R documantation and some online webpage also do not work. Does anybody know what I have done wrong? Here my code # I want to use the first 6 observations for

hello, i am so glad to write you. i am dealing now with writing my M.Sc in Applied Statistics thesis, titled " Data Mining Classifiers and Predictive Models Validation and Evaluation". I am planning to compare several DM classifiers like "NN, kNN, SVM, Dtree, and Naïve Bayes" according to their Predicting accuracy, interpretability, scalability, and time consuming etc. I have

Hello, I have two Random Forest (RF) related questions. 1. How do I view the classifications for the detail data of my training data (aka trainset) that I used to build the model? I know there is an object called predicted which I believe is a vector. To view the detail for my testset I use the below-bind the columns together. I was trying to do something similar for my trainset but

Hi Did you try google? I got several answers using your question e.g. https://stackoverflow.com/questions/54687321/fill-area-between-lines-using-g gplot-in-r Cheers Petr > -----Original Message----- > From: R-help <r-help-bounces at r-project.org> On Behalf Of Luigi Marongiu > Sent: Friday, October 23, 2020 9:59 AM > To: r-help <r-help at r-project.org> > Subject: