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 does scikit-learn perform $\chi^2$ feature selection on non-categorical features?
I'm experimenting with $\chi^2$ feature selection for some text classification tasks. I understand that $\chi^2$ test checks the dependencies B/T two categorical variables, so if we perform $\chi^2$ ...
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51 views
the effects of feature matrix format on the training time of LIBSVM
I am using Libsvm to perform text classification tasks. I normally uses binary occurrence, TF/IDF to build feature set for the input documents. It normally takes quite longer for Libsvm to finish ...
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113 views
SVM failing entirely with when test set is varied
I am experiencing a strange problem with varying the test set size.
This is mildly confusing to explain, but I'll do my best. I'm using octave to train an SVM on timeseries-like data and it's ...
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2answers
549 views
LibSVM cost weights for unbalanced data doesn't work
I have a data set that number of negative labeled values are 163 times of number of positive labeled values so I have a unbalanced data set. I have tried that:
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53 views
Significance index of unlabeled data prediction
I have a training set used to train an SVM classifier, the model found is used to predict a dataset of several unlabeled examples.
I would like to know how to extract an index of the goodness of the ...
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65 views
Regression using SVMs
I have set of time series data tuples: {(1,22), (2, 25), (3, 18), (4, 26), ... so on}
I want to estimate Y(t+1) using support vector machine regression technique. I have found numerous publications ...
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271 views
Polynomial kernel function
Consider SMV with the polynomial kernel $k(x_1,x_2)=(\langle x_1, x_2\rangle + 1)^d,$ where $d > 1.$ Is it true that if the dataset is separated with a hyperplane then the SVM (with the kernel $k$) ...
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183 views
What are the advantages of Multiple Kernel Learning (MKL) methods?
Multiple Kernel Learning methods aim to construct a kernel model where the kernel is a linear combination of fixed base kernels. Learning the kernel then consists of learning the weighting ...
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138 views
Bias items and probability estimates in LibSVM
I have two questions in using LIBSVM
The decision function for C-support vector classification is
$$\text{sgn}\left(w^T\phi(x)+b\right)=\text{sgn}\left(\sum_{i=1}^ly_i\alpha_iK(x_i,x)+b\right)$$
...
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2answers
141 views
Transform data to a higher dimensional space
The classes are as follows:
$C_1=\{3, 3.5, 4, 4.5, 5, 5.5, 7\} \cup \{15, 16, 17\}$
$C_2=\{0,0.5,1,2\}\cup\{8,9,10,11,12,13\}\cup\{20,25,30\}$
And we wish to classify numbers from the interval ...
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1answer
64 views
SVM decision function
our decision function e.g. in SVMs for binary classification (where the response is labeld by $y_i \in \{-1,1\}$) has the form:
$f(\mathbf{x}) = \text{sgn}(\mathbf{w}^\top \mathbf{x} + b)$ where ...
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2answers
108 views
Increasing the sample size does not help the classification performance
I am training a SVM classifier based on a given document collections. I started from using 500 documents for training, then I add another 500 for training, and so on. In other words, I have three ...
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2answers
126 views
Where does the definition of the hyperplane in a simple SVM come from?
I'm trying to figure out support vector machines using this resource. On page 2 it is stated that for linearly separable data the SVM problem is to select a hyperplane such that $\vec{x}_i\vec{w} + b ...
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138 views
Given a set of points in two dimensional space, how can one design decision function for SVM?
Can someone explain me how one goes about designing a SVM decision function? Or point me to resource that discusses a concrete example.
EDIT
For the below example, I can see that the equation $X_2 = ...
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38 views
How to draw a balanced random sample given prediction confidence and model performance?
INTRO
I have trained a SVM model based on 300 training cases in order to build a filter that should help me extract a bigger and evenly balanced training set, that is to be validated by human judges.
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1answer
107 views
How to combine a SVM classifier and a Naive Bayes classifier
I have two different set of features for which I have a SVM classifier and a Naive Bayes classifier, respectively. If I wanted to combine these two classifiers to get a better prediction, what option ...
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96 views
SVM with svm and svmpath function
I am trying to compare the R functions svm (library: e1071) and svmpath (library svmpath).
...
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57 views
What are hidden Markov support vector machines?
What are hidden Markov support vector machines, and how do they compare/relate to HMMs and SVMs?
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64 views
How many parameters does a HM-SVM require?
How many parameters does a Hidden Markov Support Vector Machine require?
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117 views
SVM hyperplane equation
I am trying to understand the hyperplane of the SVM algorithm. My problem is that different sources state different equations.
Which equation is the right one and if both are right, why?
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1answer
199 views
What is “feature space”?
What is the definition of "feature space"?
For example,
When reading about SVMs, I read about "mapping to feature space".
When reading about CART, I read about "partitioning to feature space".
I ...
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98 views
Kernel SVM in primal training with Stochastic Gradient Descent
In short: I am currently reading Online Learning with Kernels (http://books.nips.cc/papers/files/nips14/AA33.pdf) for fun and I can't figure out how he got to equation 8 from equations 6 and 7.
The ...
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2answers
590 views
$\nu$-svm parameter selection
For the $\nu$-SVM (for both classification and regression cases) the $\nu \in (0;1)$ should be selected.
The LIBSVM guide suggests to use grid search for identifying the optimal value of the $C$ ...
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1answer
191 views
Do categorical variables have to be dummy coded in SVM?
I am using R with the packages kernlab / caret and doing some analysis with SVM (ksvm).
I am using a Radial Based kernel for classification.
I have a few ...
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2answers
100 views
Where can I find information for variable descriptions
I have been working in R the last few weeks and have been tinkering with forecasting/predicting values for the financial data.
Is there a good place to find out what the different variables ...
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1answer
136 views
Identifiying performance of individual feature components in accuracy of support vector methods
I'm using support vector regression (not classification) for a problem and it's working well.
However, in the older method that former lab members developed (a basic linear model, with weights ...
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1answer
59 views
How can I generate data from a SVM?
I would like to generate samples from a support vector machine, with a Gaussian kernel and a fixed C and sigma? For examples ...
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1answer
73 views
SVM optimization problem
I think I understand the main idea in support vector machines. Let us assume that we have two linear separable classes and want to apply SVMs. What SVM is doing is that it searches a hyperplane ...
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1answer
1k views
How to select best kernel parameters for radial basis function of SVM with fingerprint recognition?
Here, I am using RBF function of SVM for fingerprint verification and matching. Please tell me What is the approximate range of sigma and gamma values in RFB for fingerprint recognition.
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2answers
251 views
training approaches for highly-imbalanced data set
I have a highly-imbalanced test data set. The positive set consists of 100 cases while the negative set consists of 1500 cases. On the training side, I have a larger candidate pool: the positive ...
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1answer
85 views
Regarding redundant training data in building SVM-based classifier
To build a SVM-based classifier, I have a training data set consisting of N data points. Some of them are redundant. For instance, there have 50 data points which are exactly the same, and there have ...
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139 views
Calibrating multiple binary SVM classifiers for one-vs-all multi-class classification
I'm classifying text using the one-vs-all approach. There are three classes. I've trained 3 different binary SVM classifiers using 10-fold cross-validation. The accuracy of the binary classifiers ...
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115 views
Kernel in PenalizedSVM R package
There is not option to select kernel in penalizedSVM R package. What kernel do they use?
Is there some other R package with penalized SVM methods where I can choose various kernels?
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1answer
103 views
Prediction using machine learning
Say I have some data for past 5 years and I have trained my classifier (anything decision tree, svm etc.) based on that i.e. given the appropriate input feature data and correct output labeling.
Now ...
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2answers
86 views
Meaning of 0-weighted linear weights in SVM
I am working with linear SVM (Using SVMlight) and I'm assisting to a weird phenomenon.
The training algorithm weighted some features 0. Does that means such features are irrelevant for the ...
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71 views
Multiclass classification with SVM a question about the feature vectors
I was told I had to direct my machine learning questions to this site. So here it goes.
I'm trying to do Multiclass classification with SVM. I have 7 classes. Now I was wondering if the following is ...
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1answer
196 views
Nelder-Mead simplex (fminsearch) and crossvalidation (cvpartition) with a nested function approach - Valid?
I have a binary classification problem with a somewhat balanced training set ( 665 TP 568 TN). SVM is the classifier of choice, and I am trying to optimize the hyperplane parameters $c$ and $g$ using ...
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1answer
106 views
SVM retrain on whole dataset for final model --> overfitting?
i am training a SVM (RBF kernel) with a dataset of ~1500 samples (balanced) using fminsearch on the CV error for parameter optimization (C and s).
After i found the "best" parameters (local optima ...
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1answer
883 views
Output of linear SVM model in Matlab using SVM-light
I am using SVM-light with Matlab, for linear SVM. I would like to understand the output model, but I cannot find any documentation or help about it.
Here is the output:
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123 views
comparing KNN with SVM on ROC chart
1) I wish to compare the performance of KNN and SVM on ROC chart.
a)For KNN, I obtained a linear line on ROC Chart instead of curved one.From x=0 until x=0.275, y= 0.65 and from x=0.35 until x= 0.95, ...
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458 views
About SVM cost and gamma parameters tuning
I am using R and e1071 package to tune a C-classification SVM.
My question is: regardless of the kernel type (linear, ...
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2answers
367 views
Kernel logistic regression vs SVM
As is known to all, SVM can use kernel method to project data points in higher spaces so that points can be separated by a linear space.
But we can also use logistic regression to choose this ...
3
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1answer
165 views
Can an svmlight model be converted to work with libsvm?
I have a model file that was created using svmlight in classification mode with a linear kernel. Is it possible to convert this file so that libsvm can use it for classifying?
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72 views
Which search range for determining SVM optimal parameters?
I am using SVM for classification and I am trying to determine the optimal parameters for linear and RBF kernels. For the linear kernel I use cross-validated parameter selection to determine C and for ...
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1answer
466 views
Non-linear SVM classification with RBF kernel
I'm implementing a non-linear SVM classifier with RBF kernel. I was told that the only difference from a normal SVM was that I had to simply replace the dot product with a kernel function:
$$
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2answers
692 views
Problem with e1071 libsvm?
I have a dataset with two overlapping classes, seven points in each class, points are in two-dimensional space. In R, and I'm running svm from e1071 package to build separating hyperplane for these ...
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4answers
225 views
comparing predictive model with hold out set
In Rapid Miner, I created a predictive model (SVM) with Kernel type = polynomial, c= 10, and obtained 80.77% accuracy using cross validation. When compared to hold out set my accuracy on the test ...
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69 views
Same (poor) results with linear and non-linear classifiers
I am doing classification of "text quality" using four classes and using 30 features with 1300 samples. I am using the following classifiers:
LDAC based on linear discriminant analysis from mlpy.
...
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42 views
SVM for matching prediction
I have a set of instances, where each pair is labeled with as match or non-match.
For each instance $I$, I extract several feature vectors $\{F_1(I), ..., F_N(I)\}$.
For each pair of instances ...
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77 views
Best way to classify hierarchical data
First of all, I want to be clear that I am new to AI, although I've learned a bit about classification.
Let's say I have a hierarchical sets of words:
...
