Tagged Questions

Support Vector Machine refers to "a set of related supervised learning methods that analyze data and recognize patterns, used for classification and regression analysis."

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How to do cross-validation when comparing different feature selection methods?

I am using SVM for a prediction task. My sample size is small, only N=140. Suppose I want to compare the prediction accuracy when using two different feature selection methods. Would it be better to: ...
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2answers
36 views

Does Support Vector Machine handle imbalanced Dataset?

Does SVM handles imbalanced dataset? Is that any parameters (like C, or misclassification cost) handling the imbalanced dataset?
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7 views

One Class SVM Training in LIBSVM

Could you kindly reply my queries in context of using LIBSVM for One class SVM. Assuming I have samples from one class only, do I need to put a lable for each sample...but a training file without ...
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6 views

LibSVM totalSV for multiclass

I am performing classification of K=9 classes using linear SVM with libSVM (MATLAB warp) I am using 400 samples of data to perform the training and I'm getting: totalSV: 203 I know libSVM uses ...
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10 views

Does the gamma hyperparameter have any affect on a polynomial SVM?

I am using sklearn and its SVM implementation - But I was wondering whether the gamma parameter was a parameter exclusive to the rbf kernel; since the gamma parameter indicates the width of the ...
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15 views

SVM - RFE for nonlinear case

Could someone give me some reference or idea on how to implement SVM-RFE for nonlinear cases. As we all know that SVM RFE for linear case is well established by Guyon et al. for (gene) selection where ...
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17 views

Support Vector Machine with zero bias term

I'm looking for an algorithm to solve SVM with zero bias term. So dual form of such SVM is $max_\alpha \sum_i^n \alpha_i -1/2\sum_i^n \sum_j^ny_iy_jK(x_ix_j)\alpha_i\alpha_j$ subject to: $0 \leq ...
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0answers
8 views

SVM tends towards one class

I implemented a 1 vs all multi class SVM using libsvm. When I use the trained SVM to predict it will just assign all the samples to the class that is most abundant. Is there a chance that the data I'm ...
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10 views

How do I install and use Shogun toolbox in matlab? [closed]

I want to use Shogun toolbox in matlab (windows) but their installation guide is not clear. Does anyone know simple steps to install shogun toolbox in matlab?
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12 views

The Shogun Machine Learning toolbox for SVM with precomputed kernel and zero bias

Can I use the Shogun Machine Learning toolbox for SVM with precomputed kernel and zero bias. I should be able to input pre-computed kernel and I also should be able to set bias zero.
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11 views

SVM with pre-computed kernel and zero bias

I have an optimization function, where I need to give my own kernel matrix and bias value is zero. The kernel matrix is calculated using the data but there is no specific formula for it. If I have a ...
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1answer
19 views

libsvm: scaling data results in less features?

I've scaled my training and testing data in BASH like so: ...
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3 views

How to account for different ratio of samples during training and detection using a support vector machine (svm)?

Consider the following object recognition case: Detection of objects in an image using a sliding window approach in combination with a svm model. During sliding window search using multiple scale ...
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12 views

How to find a good model for an object recognition case using a support vector machine (svm)?

Consider the following example of an object recognition case: I'm trying to detect objects in an image using histograms of oriented gradients (hog) features. The feature vector resulting from hog is ...
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11 views

Optimizing Lagrangian for SVM Alpha Values

So I have some understanding of how to optimize Lagrangian functions for single values. But for a support vector machine (SVM) we have: $$L = \sum_{i=1}^N \alpha_i - ...
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24 views

Heavy-tailed RBF kernel function

I'm trying to run a SVM regression on some data and I want to use ksvm from kernlab or svm ...
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1answer
41 views

Probability distribution of Y in regression?

I'm trying to predict the probability distribution of $Y$ given $X_0, X_1, ...$ with a nonlinear regression. The probability distribution of $Y$ is likely not normal. So far, I've set up and trained ...
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26 views

What is the relationship between vector space models & support vector machines?

Is there a relation between them? Specifically, if I have a VSM can I classify it through SVM?
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4 views

SVR overfitting

I´m using epsilon-SVR, and after a 5 cross, and testing it with an external set: ...
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9 views

LIBSVM for pre-computed kernel and zero bias (b values is zero)

I want to do binary classification and I'm using LIBSVM library for that. I have a precomputed Kernel and my bias value (b) is zero. Can I do this in LIBSVM or do I have to use some other library? ...
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26 views

Does Text Classification using SVM needs to use a dictionary to build the features vectors?

I'm kinda new to this, but I want to do an experiment I need your guys help. Open to all suggestions. Let's say I have around 5000 user accounts for which I only have several attributes [first name, ...
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29 views

Predictive model with combinations of dummy variables of different length

I would like to try to predict the amount of a public contract based on historic records where the main variables that I can fit against include: contact duration (continuous) number of buyers ...
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0answers
13 views

Usage of libsvm with RBF kernel and no Offset

I'm using libsvm for the binary classification and using a precomputed Kernel. In my particular problem there is no bias term (it's zero). Is there anyway to adjust the bias term in libsvm (and not ...
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12 views

Weka SMOreg and LIBSVM with linear kernel problems

I want to test a dataset in weka using either LIBSVM with an e-SVR or SMOreg for regression. I also choose a linear kernel in both (in SMOreg i use an exponent=1 in a non normalized polykernel). ...
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1answer
16 views

What is the toolkit that implements Cost sensitive Support Vector Machine?

I need implementation of cost sensitive support vector machine. The cost is different for each training example (unlike each class). So problem is to solve $max_\alpha$ $-1/2 \sum_{i,j} ...
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13 views

definig distances using radial basis functions

in svm the kernels are supposed to measure the distance between two vectors in the feature space. however, rbf is largest at 0 meaning that in that new space the distance between a feature and itself ...
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12 views

SVM Multiclass probability distribution

I have the following probability distribution (-b output of libsvm): ...
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1answer
43 views

Support vector regression versus kernel ridge regression

I have a question concerning the difference between support vector regression and kernel regression. I will try to write down all the math so no misunderstandings arise (hopefully). Let's begin with ...
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2answers
59 views

bad results with SVM

I have a dataset of 1157 samples. The number of features are 6 and I have only one output. My training error is very poor although I have tried a wide range of cost values and followed the recommended ...
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18 views

SQL query optimization using machine learning

This is related to my thesis work. I am trying to use SVM for query optimization. After finding the best query plan, I have to train the machine so that whenever the same type of query appears the ...
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1answer
30 views

Data normalization in k-means and svm

Generally if I want to normalize my data in which direction I should normalize (subtracting mean and dividing by std)? Lets say I have a data matrix D (...
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2answers
67 views

Why does the scaling of feature vectors improve performance of SVM classifier?

I've found that performing scaling in SVM problems really improves the performance of SVM ... But I don't understand why! I have read this explanation: "The main advantage of scaling is to avoid ...
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14 views

How we can statistically compare performance of two models before and after outlier detection?

As you know we can use Mcnemar's test to compare performance of two models in binary classification problem. But in my case i ...
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0answers
15 views

Why SVM with RBF is similar to KNN with prototypes search?

I explored similar questions and everything I can see is that both kNN and RBF are non-parametric methods to estimate the density of probability of your data. However, I am not sure if this has ...
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11 views

What is the relationship between separable SVM test error bounds and soft-margin SVM test error bounds?

Can I compute the bounds for a soft margin SVM by taking the VC dimension for an SVM and using the misclassified examples as train error? Does the inequality from wikipedia's VC dimension page hold ...
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21 views

Intuition on One Class Support Vector Machines

I am having trouble understanding how one-class SVMs work. They were introduced in a paper by Scholkopf and others (and can be found here). One-class SVMs perform "novelty detection", where a point ...
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19 views

Handling outliers in the target variable

I'm using a support vector regression model. I know the target variable has some outliers and modeling the data directly leads to bad results (Rsquare close to 0.2). I'm pretty sure the outliers are ...
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2answers
38 views

Suitabiility of the confidence score generated by SVM as a proxy for membership function

SVMs can generate a confidence score which is basically like a probability for a particular data item to belong to the particular class. I want to use this probability as a proxy for the 'distance' of ...
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21 views

Use cases for P-Kernel for SVMs

I've been reading the book by Cristianini on Kernels (2004) where generative kernels (like p-kernel and fisher-kernel, not to be confused with polynomial kernel!) are described. I am interested in ...
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38 views

predicting time series with support vector machine using R

I am planning to do time series prediction using support vector Machine. I could not find any materials about time series application of support vector machines using R or Mat-lab. Similar question ...
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2answers
56 views

Varying LIBSVM predictions based on test series labels

So I have a pretty well testing SVC train series which puts me into the mid 80 percentile without outrageous C/g values. My current C value is 2.0 and gamma is 0.5. Good numbers across the range ...
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1answer
46 views

How to prepare my data for SVM classifier in matlab

I am new to SVM and Matlab. I would like to have an example how to prepare my data to be as input to the SVM classifer (using libsvm) let us assume that i have a group of words first i have ...
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19 views

Combined Two CLassifiers

I am involved in a research where i need to classify group of words (strings) into two classes I am currently reached a dead point where my classifier is not doing as i expected. I used like three of ...
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0answers
22 views

Live selection of movie to suggest based on similarity of users

I am working with movie selection for users. 1 ) One of the first ways I thought was taking all the clicked only movie data and building decision trees out of it. Then when input is passed, the ...
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29 views

Support vector regression - data visualization

I have some training set (y1, x1) , (y2, x2), ..., (yn, xn). Output yi is a real number and the features xi live in a real d-dimensional space. I am here in the high dimension case where n = 30 and d ...
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2answers
58 views

One Class SVM strange decision boundary

I am trying to plot the decision boundary of a One Class SVM. This is a 2 dimensional representation of my training data And here the picture of the prediction obtained on the training data ...
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0answers
9 views

Linear-time approximation to kernel SVM?

Scaling kernel support vector machines to large datasets is a very challenging problem. For linear SVMs, PEGASOS is able to learn efficiently online, so training time scales linearly with the size of ...
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0answers
11 views

How do i generate variables that are relevant only for some classes?

I want to generate data for classification. I've generated data with 10 variables with two are relevant for all classes and 8 noise. now, I want to generate variables that are relevant just for some ...
1
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1answer
58 views

Selecting most realistic C and g params after gridsearch

I just ran an extended SVC gridsearch in libsvm on about 9000 multi-dimensional vectors representing a time series. Here are the highest scoring results: ...
0
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1answer
56 views

Logistic Regression, SVM or NN?

Just attended Andrew Ng’s online course on ML and although I’ve understood the methods I seem to be missing the intuition on where to apply them in terms of classification problems. What are the ...