svm

Best MATLAB toolbox that implements Support Vector Regression?

In this Wikipedia article about SVM there are a number of links to different implementations of MATLAB toolboxes for Support Vector Machines. Could anyone suggest which of these is best in terms of speed, ease of use, etc.? ...

How do you resolve issues with named pipes?

I have a binary program* which takes the contents of a supplied file, processes it, and prints the result on the screen through stdout. For an automation script, I would like to use a named pipe to send data to this program and process the output myself. After trying to get the script to work I realized that there is an issue with the bi...

Multivariate mapping / regression with objective function

Overview I have a multivariate timeseries of "inputs" of dimension N that I want to map to an output timeseries of dimension M, where M < N. The inputs are bounded in [0,k] and the outputs are in [0,1]. Let's call the input vector for some time slice in the series "I[t]" and the output vector "O[t]". Now if I knew the optimal mapping ...

Pointers to some good SVM Tutorial ...

Hi all, I have been trying to grasp the basics of Support Vector Machines, and downloaded and read many online articles. But still am not able to grasp it. I would like to know, if there are some nice tutorial sample code which can be used for understanding or something, that you can think of, and that will enable me to learn SVM B...

How do I plot a classification graph of a SVM in R

I have an svm in R and I would now like to plot the classificaiton space for this machine. I have found some examples on the Internet, but I can't seem to make sense of them. My R script is as follows: library(e1071) day_of_week <- c(0,1,2,3,4,5,6) holiday <- factor( c(T, F, F, F, F, F, T) ) model <- svm(day_of_week, holiday) plot(mode...

Know any good c++ support vector machine (SVM) libraries ?

Hey everyone, Do you know of any good c++ svm libraries out there ? I tried libsvm (http://www.csie.ntu.edu.tw/~cjlin/libsvm/) but so far I'm not flabbergasted (no documentation, or close to none). I have also heard of SVMLight and TinySVM. Have you tried them ? Any new players ? Thanks ! JC ...

Help using predict() for kernlab's SVM in R?

I am trying to use the kernlab R package to do Support Vector Machines (SVM). For my very simple example, I have two pieces of training data. A and B. (A and B are of type matrix - they are adjacency matrices for graphs.) So I wrote a function which takes A+B and generates a kernel matrix. > km [,1] [,2] [1,] 14.33333 18....

Unsupervised classification methods available

Hi all I'm doing a research which involves "unsupervised classification". Basically I have a trainSet and I want to cluster data in X number of classes in unsupervised way. Idea is similar to what k-means does. Let's say Step1) featureSet is a [1057x10] matrice and I want to cluster them into 88 clusters. Step2) Use previously cal...

Implementing a linear, binary SVM (support vector machine)

I want to implement a simple SVM classifier, in the case of high-dimensional binary data (text), for which I think a simple linear SVM is best. The reason for implementing it myself is basically that I want to learn how it works, so using a library is not what I want. The problem is that most tutorials go up to an equation that can be s...

Any python Support Vector Machine library around that allows online learning?

I do know there are some libraries that allow to use Support vector Machines from python code, but I am looking specifically for libraries that allow one to teach it online (this is, without having to give it all the data at once). Are there any? ...

Weights from linear SVM model (in R)?

Using kernlab I've trained a model with code like the following: my.model <- ksvm(result ~ f1+f2+f3, data=gold, kernel="vanilladot") Since it's a linear model, I prefer at run-time to compute the scores as a simple weighted sum of the feature values rather than using the full SVM machinery. How can I convert the model to something li...

How to do multi class classification using Support Vector Machines (SVM).

Hello, In every book and example always they show only binary classification (two classes) and new vector can belong to any one class. Here the problem is I have 4 classes(c1, c2, c3, c4). I've training data for 4 classes. For new vector the output should be like C1 80% (the winner) c2 10% c3 6% c4 4% How to do th...

Data Classification:sizes of training and test vectors

Hi I have an application which decides whether a human is handwaving,running or walking. The idea is i have segmented an action,say handwave,to its poses. Let's say Example; for human1:pose7-pose3-pose7-..... represents handwave for human3:pose1-pose7-pose1-..... represents handwave for human7:pose1-pose1-pose7-..... represents handwa...

"Confidence score" for each point in SVM using Kernlab?

Hi, I've created a kernel regression model (though this question would work with a SVM classification model as well). I'd like to determine the distance between the point and the hyper-plane for each point. Does anyone know if kernlab returns this or is there another R-based SVM package I could use? Thanks ...

How do I get ruby-svm to look for libraries in macports' /opt/local?

I want to install Ruby SVM. I already have macports with normal settings, and installed libsvm via port just fine. But when I go to compile rubysvm, it barfs. :( Ruby SVM: http://rubysvm.cilibrar.com/download/ (most links are 404 though) libsvm: http://www.csie.ntu.edu.tw/~cjlin/libsvm/ Try this: sudo port install libsvm wget http://d...

How to approach machine learning problems with high dimensional input space?

How should I approach a situtation when I try to apply some ML algorithm (classification, to be more specific, SVM in particular) over some high dimensional input, and the results I get are not quite satisfactory? 1, 2 or 3 dimensional data can be visualized, along with the algorithm's results, so you can get the hang of what's going on...

training time and overfitting with gamma and C in libsvm

Hi, I am now using libsvm for support vector machine classifier with Gaussian kernal. In its website, it provides a python script grid.py to select the best C and gamma. I just wonder how training time and overfitting/underfitting change with gamma and C? Is it correct that: suppose C changes from 0 to +infinity, the trained model wi...

SVM Classification - minimum number of input sets for each class

Im trying to build an app to detect images which are advertisements from the webpages. Once I detect those Ill not be allowing those to be displayed on the client side. From the help that I got here in stackoverflow, I thought SVM is the best approach to my aim. So, I have coded SVM and an SMO myself. The dataset which I have got from ...

Error plotting SVM classification graph

I'm using the support vector machine from the e1071 package to classify my data and want to visualize how the machine actually does the classification. However, when using the plot.svm function, I get an error that I can't resolve. Script: library("e1071") data <-read.table("2010223_11042_complete") names(data) <- c("Class","V1", "V2"...

Optimizing SMO with RBFKernel (C and gamma)

There are two parameters while using RBF kernels with Support Vector Machines: C and γ. It is not known beforehand which C and γ are the best for one problem; consequently some kind of model selection (parameter search) must be done. The goal is to identify good (C;γ) so that the classier can accurately predict unknown data (i.e., testin...