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 do interpret statistically NULL SVM Output

I am using LibSVM (3.18) as an implementation of SVM. But every time when I'm predicting the result, it's giving zero. I am following these instructions: I have CSV file (+50K lines), Most of data ...
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7 views

Normalization for pattern classification?

I'm working off my first independent project for some pattern classification. I'm utilizing some datasets from UCI machine learning, but am not sure on how to start with data normalization. The data ...
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30 views

SVM for unbalanced data

I want to attempt to use Support Vector Machines (SVMs) on my dataset. Before I attempt the problem though, I was warned that SVMs dont perform well on extremely unbalanced data. In my case, I can ...
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8 views

Difference between ep-SVR and nu-SVR (and least squares SVR)

I am trying to find out which SVR is suited for what kind of data. I found out 4 types of SVRs: epsilon, nu, least squares and linear. I understand linear SVR is more or less like lasso with L1 Reg. ...
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37 views

Convert maximization problem to minimization

I am looking at the derivation of the Maximal Margin Classifier model, where they typically transform the following maximization problem: into this minimization problem: Why is maximizing ...
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28 views

SVM data normalization… what about classifying new (training) data?

I've got a big doubt about SVM classification task (and more in general classification task), about data normalization. Let's suppose I've a SVM trained with normalized data, and new data to classify. ...
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55 views

Does using a kernel function make the data linearly separable?

I'm reading about SVM and I learned that we use a kernel function so the data become linearly separable in the high dimensional (vector?) space. But then I also learned that they use the soft-margin ...
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11 views

Multi-class semi-supervised classification code (SVM, co-training, Graph-based)?

I am trying to evaluate the performance of my semi-supervised algorithm, by comparing it against different algorithms. I have searched a lot, but can't find code that does multi-class semi-supervised ...
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3 views

Liblinear types of solver

There is many variants of type of solver in liblinear but I don't understand their differences.Which one I must choose? Also why data must be scaled? duo to some numerical issues? ...
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11 views

Is it possible prediction of chemical activity with few data?

I have activity data (represented by a real number) for five chemical compounds (and for which I have a set of 600 descriptors) and would like to use neural networks or SVM or any other system that ...
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22 views

Response surface of a particular discontinuous function

I have a function IR that depends on several (maybe 100) input random variables. I know ...
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25 views

Finding best parameters of SVM in matlab

I’m designing a system (using Matlab) that I can optimize parameters of a support vector machine (SVM) with genetic algorithm, harmony search and another optimization algorithms to find the best ...
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25 views

Outlier detection in binary classification

I have a question about outlier detection in my system. I’m designing a system (in Matlab) that optimize both features and parameters of a classification method (like mlp) together with optimization ...
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13 views

Rank features by predictive power in trained classifier (LibSVM)

I'm training a SVM classifier on a dataset using LibSVM through Weka, but after I have my trained classifier I'd like to know which features are important to my classifier and which features don't ...
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26 views

SVM kernel parameters?

Hayy all,, Im going to do classification using SVM. As I understand we have to project our data into higher dimensional by using kernel. And there are 4 common use kernel (linear, RBF, polynomial, and ...
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22 views

On the stopping criterion of coordinate descent method for linear SVM with $\ell_1$-regularization

I am trying to implement the coordinate descent method to solve the dual of linear SVM problem, but blocked at the stopping criterion. The dual of linear SVM problem is: $$\min f(\mathbf{x}) = ...
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25 views

SVM decision boundary conditions : derivation problem

I was trying to understand the derivation of SVM decision boundary. Suppose my decision boundary is y-x-1=0. Now in the book it was written that ...
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1answer
46 views

Pegasos prediction time

I have been implementing the (kernelized) Pegasos algorithm, but am running into problems in terms of scalability. I will use notations as in the original manuscript. Here's a typical time ...
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35 views

HOG Feature Implementation with SVM in MATLAB

I would like to do classification based on HOG Features using SVM. I understand that HOG features is the combination of all the histograms in every cell (i.e. it becomes one aggregate histogram). ...
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16 views

SVM without offset

I would like to know if the linear-SVM-without-offset solver: $$\min \frac{1}{2}\|w\|^2+C\sum_{i=1}^m \xi_i, \quad \mbox{s.t.}\quad y_iw^\top x_i \geq 1-\xi_i, \quad \xi_i\geq 0 \quad \forall ...
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25 views

Scaling/Normalisation or Standardization

I'm working on SVM and ANN classification tools. In order to improve the classification accuracy, I want to know the best or the recommended data-preprocessing, is it scaling/normalisation or ...
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How Does a Disparity in Number of Documents (Training Data Points) Affect Text Classification?

I have collected a fairly clean set of data (5,410 documents) to train a text classifier. I am now attempting to improve my classification success. (Note: When I trained/tested the classifier from ...
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15 views

Is support vectors algorithms dependent?

In SVC problem, given all the coefficients fixed (C, gamma, etc), is it possible to get different decision functions and support vectors with different optimization strategies?
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19 views

Derive squared exponential covariance function

In Gaussian Processes, SVMs, kernels are used (as to my understanding) as similarity measure. However, they have the constraint that any kernel has to be represented as a dot product. i.e. ...
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25 views

Support Vector Machines - Kernel Functions/Soft Margin SVM

I had these questions in an exam today. State True or False and explain. If k1(.,.) and k2(.,.) are two valid kernel functions, then if h = k1 - k2, is h(.,.) a valid kernel function? A standard ...
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25 views

libsvm: Cross Validation with imbalanced classes

I am using libsvm for a 2-class classification problem. For my testing I use the C-SVM with RBF kernel. My main problem seems to be that the classes are highly imbalanced. While I have 35000 datasets ...
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31 views

R package kernlab probabilities seem not to match decision

For a classification problem I am giving the R package kernlab a shot – not the least because it offers to calculate class probabilities instead of only a plain decision. However, comparing results ...
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17 views

modeling rates with machine learning tools (svm, gbm, nnet)

I have a numeric integer variable that is knowly proportional to an exposure measure plus other continuous / categorical covariates. If I were to use classical log-linear glms i would model ...
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when do i give up on a R program? [migrated]

i am using the library, e1071. in particular, i'm using the svm function. my dataset has 270 fields and 800,000 rows. i've been running this program for 24+ hours now, and i have no idea if it's hung ...
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27 views

Normalized Data vs. Non Normalized Data in SVM Training

Im training an SVM on a dataset containing 17000 events with 30 features. as I see it, this amount of features against the dataset size should suffice by itself for avoiding overfitting. Im training ...
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26 views

How to build feature vectors from profile data

I want to build feature vectors from data of my test set, which contains profiles of people. I always want to compare two profiles to each other. Thus my features are: - Same surname ∈ {undefined, ...
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How do I get the support vectors data (the model file) when using cross validation in LibSVM? [migrated]

I have a problem with the output file when I use ./svm-train ... -v k When I use the parameter -v, the output file doesn't get created, but I need the support ...
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87 views

Deriving the optimal value for the intercept term in SVM

I was reading andrew ng's machine learning lecture notes on SVM. I came across the following equation (finding the optimal value for the intercept term $b$ in the SVM problem): However, I have no ...
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29 views

Understanding the geometric margin of SVM

I was watching andrew ng's lecture on machine learning and I came across 'geometric margin' in the SVM lecture. I am confused about he obtained the equation for the point B ? Notice that the ...
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26 views

One vs All and One vs one in svm?

What is the different between onee vs all and one vs one SVM classifier?? Is One vs All mean = 1 classifier to classify all types /categories of the new image and one vs one mean= each type /category ...
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What's wrong with the intuition that kernel measures similarity between observations?

Near the middle of page 16 of Andrew Ng's notes on SVM, he explained an intuitive view of kernel as measuring similarity between observations, but then added the caveat that there are things wrong ...
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26 views

What is parameter fine tuning means in SVM?

I got this sentence in one of paper, but I dont understand what does it mean?? " Training a learningbased classifier such as an SVM on an imbalanced dataset often requires parameter fine-tuning, ...
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18 views

Returning the inverse of a matrix in a quadratic program (SVM) in cvx optimization package

I am solving the dual QP of an SVM, and using the RBF kernel. As you know, the objective function is of the form $$f(\alpha) = \alpha^T Q \alpha $$ where $\alpha$ is the optimization variable and $Q$ ...
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129 views

The difference of kernels in SVM?

Can someone please tell me the difference between the kernels in SVM: Linear Polynomial Gaussian (RBF) Sigmoid Because as we know that kernel is used to mapped our input space into high ...
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1answer
65 views

SVM basic theory?

I have some questions about SVM: In SVM there is a nonlinear and linear SVM. What is the difference between them? To do classification in SVM, we will find the linearly separable boundary ...
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38 views

Is the value of $\alpha$ the same for all support vectors (SV) in the dual and what is the reason for it if they do or don't?

Consider the dual with no offset and not slack. In the dual we have that for data points that are support vectors: $$\alpha_t > 0$$ and that the constraint is satisfied with equality (since a ...
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24 views

Different formulations for SVM with slack variables (primal)

I have seen two different ways to formulate the SVM optimization but I was not sure what the difference was between them or if there was any difference. First formulation: $$min ...
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1answer
50 views

Type of regression method to use

I have the marker data of 32 patients for eight different markers. WHat needs to be done here is to predict the type of marker which is suitable for the disease control. I used Disease control as the ...
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13 views

Imbalanced values in the feature set of training and testing samples in SVM (Multi class classification)

Currently I only know about the imbalanced in the structure of data set (e.g. too many positive samples, few negative samples..). But how about imbalanced in the value of features in each samples? For ...
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60 views

SVM primal formulation: does the constants constraint matter?

When finding the maximum margin separator in the primal form we have the quadratic program $$min\frac{1}{2}||\theta||^2$$ $$\text{ subject to: } y^{(t)}(\theta \cdot x^{(t)} + \theta_0) \geq 1, \ ...
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27 views

How to give the input of an image to SVM after preprocessing

I got a dataset of images(GRAZ_02 Data set-Cars,Bikes,People) and extracted features from each and every image in the database using a descriptor(SIFT algorithm) that returns a matrix of order :(No. ...
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15 views

Why even my training data failed during the prediction of libsvm [duplicate]

Currently I'm using libsvm for my one class classification problem. I have 10 samples in my training set, 5 samples in my testing set, both of my training and testing set is scaled by svm_scale, then ...
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37 views

Libsvm includes training data in testing file

Currently I'm using libsvm (Java) for my one class classification problem. I scaled both of my training data and testing data by svm_scale, the problem is that somehow,libsvm includes both training ...
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56 views

Multi class classification always have better result than one class classification?

Currently I'm using svm to classify the test samples to two different classes (True and False). When I use multi class classification, I have both true and false samples in my training set, the ...
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1answer
84 views

What is SVM regression? Is it for regression or classification?

I'm trying to understand what is SVM regression. It's used for classification or regression? Can someone give an intuitive understanding of it?