0
votes
1answer
31 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 ...
0
votes
0answers
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 ...
0
votes
1answer
24 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 ...
1
vote
0answers
12 views

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 ...
0
votes
0answers
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?
1
vote
0answers
24 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 ...
0
votes
0answers
15 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 ...
0
votes
0answers
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, ...
0
votes
1answer
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 ...
2
votes
2answers
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 ...
3
votes
1answer
62 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 ...
5
votes
1answer
37 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 ...
1
vote
1answer
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 ...
0
votes
0answers
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 ...
3
votes
1answer
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, \ ...
0
votes
0answers
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 ...
0
votes
1answer
83 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?
2
votes
1answer
40 views

Dimension of weight vectors in SVMs

For a given set of features (say with dimension a) and for a given set of labels (say m labels), how to relate the given features with the weight vector of the SVM in general? Will it be equal to ...
1
vote
1answer
60 views

building a classification model for strictly binary data

i have a data set that is strictly binary. each variable's set of values is in the domain: true, false. the "special" property of this data set is that an overwhelming majority of the values are ...
0
votes
0answers
34 views

Supervised or unsupervised learning problem?

currently I'm working a pattern recognition problem. I have been using supervised learning (neural network and svm with one class classification) but I think I'm doing it in a wrong way. For ...
0
votes
1answer
23 views

Statistic test on percentage correct classified by emotion recognition

For a potential emotion recognition bachelor-project I was wondering what statistical test I have to perform when I get my results to test whether it's significant. I will be testing which combination ...
0
votes
0answers
16 views

Low accuracy for training in image classification

I'm a newbie using LinearSVM to train the classifier. I labelled the images of 'buildings' as 1 and the others as -1. The training result is as follows : and As you can see in the image some of ...
0
votes
1answer
114 views

One class classification with libsvm. Accuracy results in 0%

A quick recap for what I want to do, I want to determine if a text is written by the same author or not. Thus I use one-class classification. In my training set (18 samples), it looks like this (for ...
1
vote
2answers
78 views

How to report a SVM model to a 3rd party after cross-validation?

I have a binary classification problem. I trained my dataset using a Support Vector Machine (SVM). Now I want to report the model I trained to a 3rd party so that they can use. For the primal probem ...
3
votes
2answers
113 views

k folds cross validation on a multi-class dataset

Cross validation is one of the most important tools because it gives us an honest assessment of the true accuracy of our system. In other words, the cross-validation process provides a much more ...
3
votes
0answers
36 views

Machine learning with ordered labels

The usual method for adapting binary classifiers like various SVMs to multilabel data is one-vs-all, which assumes that labels are independent and in case of a prediction error we don't care what ...
3
votes
1answer
64 views

Do fewer support vectors imply a simpler model?

I am applying $\epsilon$- and $\nu$-regression to sample data, and I discovered I had different results in terms of the count of support vectors. When I have fewer support vectors, does it mean that ...
0
votes
1answer
44 views

Goldfarb Idnani quadratic solver

I am implementing the Support Vector Regression (SVR) algorithm by means of quadratic programming. In order to do that, I am using an optimization library that contains a quadratic solver based on the ...
2
votes
1answer
54 views

libsvm_linear kernel_increasing C value

I'm using libsvm in C-SVC mode (-s= 0) with linear kernel (-t= 0), and I'm required to train multiple SVMs( I have four classes). My training and test sets have the same number of instances and ...
4
votes
3answers
189 views

Is a lower training accuracy possible in overfitting (one class SVM)

I am using the heart_scale data from LibSVM. The original data includes 13 features, but I only used 2 of them in order to plot the distributions in a figure. Instead of training the binary ...
2
votes
1answer
102 views

Monte Carlo simulation vs. machine learning algorithms: what is the difference in application?

I have been doing some research on different type of machine learning (ML) algorithms such as random forest/SVM etc. in order to model and best predict pharmaceutical needs of patients suffering from ...
0
votes
1answer
47 views

Binary classification using radial basis kernel SVM with a single feature

Is there any interpretation (graphical or otherwise) of a radial basis kernel SVM being trained with a single feature? I can visualize the effect in 2 dimensions (the result being a separation ...
0
votes
1answer
89 views

How to construct the feature weight vector (or Decision Boundry) from a linear SVM classifier from scikit?

I use the following code to train an svm classifier: clf = svm.SVC(kernel='linear') clf.fit(train_mat, train_labels) that fit the data and save the info in the ...
0
votes
0answers
29 views

Problem with classifier prediction results

I built a classifier with 13 features ( no binary ones ) and normalized individually for each sample using scikit tool ( Normalizer().transform). When I make predictions it predicts all training sets ...
0
votes
0answers
38 views

Recursive feature elimination with only two classes

Recursive feature elimination (RFE) is a feature-selection strategy. It performs in two nested levels of cross-validation. First it tries to divide the training set into N folds. RFE puts one fold ...
1
vote
0answers
20 views

kernel for a (semi-) metric space

Let's say I have a metric space $(\mathcal{X}, d)$. Is there any kernel function that I can use with SVM? If we change the RBF kernel a little bit, we have $k(x,y) = e^{-d(x,y)^2}$. Is this a valid ...
0
votes
0answers
37 views

Scaling data in machine learning algorithm

I am currently working on a linear classifier, which uses the statistical learning paradigm; that is, no knowledge about the distribution from which that training data are drawn from is available. ...
0
votes
0answers
19 views

what can be inferred from the error plot of my classifier?

I am working on a classification task where I use 12 features. My training set has 400 samples of positive data and 2000+ samples of unlabelled data. While testing has 34 positive samples and 999 ...
1
vote
1answer
183 views

Logistic Regression\SVM implementation in Mahout

I am currently working on sentimental analysis of twitter data for one of telecom company data.I am loading the data into HDFS and using Mahout's Naive Bayes Classifier for predicting the sentiments ...
1
vote
1answer
63 views

Nuisance covariate or variable of no interest in machine learning

I'm trying to differentiate two groups of patients using various machine learning algorithms, including support-vector machines (SVM). As far as the details of the analysis go, I would like to train ...
0
votes
1answer
106 views

Using LibSVM for anomaly detection

Im trying to create a one class SVM using libSVM. However whenever I run the svmpredict function it always return an accuracy of 0%. ...
0
votes
1answer
35 views

error increasing with no of estimators in adaboost

My error gets increased when i increase the n_estimators value in ...
0
votes
0answers
30 views

Proximal SVM and classification algorithms

I was trying to understand the parallel machine learning using Proximal SVM. The implementation I'm following is from atbrox.com. It was a no-brainer to execute the python script and get the output. ...
5
votes
2answers
142 views

What is meant by 'weak learner'?

Can anyone tell me what is meant by the phrase 'weak learner'? Is it supposed to be a weak hypothesis? I am confused about the relationship between a weak learner and a weak classifier. Are both the ...
3
votes
2answers
127 views

Is it possible to train a one-class SVM to have zero training error?

I'm trying to work on an anomaly detection problem, so I am currently exploring my options on which algorithm is best to use for me. I've been looking at the one-class SVM in the scikit-learn library ...
1
vote
1answer
119 views

SVM training method (or alg.)

I'm using SVM classification (Matlab) within my research works, and I want to know: The advantages and disadvantages of each training algorithm, i.e., SMO, LS and QP In general case, what is the ...
1
vote
2answers
102 views

SVM mathematical background

I try to get the basic understanding behing SVM algorithm, however I have a problem with basic mathematics. I follow the lecture Support Vector Machine. Suppose the two classes can be separated ...
1
vote
1answer
95 views

Poorness of Kernel methods on visual pattern recegnition?

I am currently reading the recent papers mainly written by Y. Bengio [1],[2],[3]. There are very strong claims about poorness of Kernel methods on recognizing handwritings in many general cases but ...
0
votes
0answers
34 views

the relationship between training set size and precision/recall

With respect to a classification problem, I once heard the following comment: Adding more positive training cases can increase the recall; and adding more negative training cases can increase the ...
0
votes
1answer
100 views

Modifying decision function in LibSVM

The decision function for C-support vector classification is $sign(wT\phi(x)+b)=sgn(\sum_{i=1}^{l}y_i\alpha_iK(x_i,x)+b)$ How can I modify it to ...