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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Can I use an SVM for labeling data as more than one class

I'm trying to classify e-mails using Mallet. If the classifier is too unsure about a new e-mail I would like a user to do the classification instead. I figured I could use the Mallet Labeling output ...
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4 views

SVM Regression x Classification parameters

What are the differences between CV for parameters search in Regression and classification in SVM ? I´m asking this, because searching for a gamma [-5,3] in classification is much more quickly than ...
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1answer
35 views

Is it better to use MAE or MSE for perfomance measure? [duplicate]

My data set is about forest fires in Portugal. I want to define a model that can predict better wildfires. In my data set, the outliers are entries referring to big fires. What is the best performance ...
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19 views

support vectors in text analytics

i am beginning to harness scikit's svm to perform some news analytics. While going through their tutorials they perform a classification (using linear SVM) on a dataset called 20 news group. I chose 4 ...
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24 views

Unclear what to make of test results

I'm attempting to classify e-mails using Mallet and an SVM. Below are some test-results, but I'm not sure what to make of them. The test-set is the most recent e-mails found per project. The ...
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8 views

svmlight for unbalanced data [closed]

I'm using svmlight for multiclass classification using one vs rest strategy. I'm having highly unbalanced data. One data set has 5000 and other set has 500.How to train this unbalanced data in ...
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23 views

What are the most interesting, new hot topics in machine learning for seminar and later for thesis? [closed]

I'm in an informatics master student in Palestine Polytechnic University, I have a seminar course this semester i cant decide the topic to search in, especially that i want it to be my thesis topic ...
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2answers
19 views

Can I use SVM classification probability for ranking?

I have used SVM for finding relevant results, denoting relevant results by class 1 and irrelevant results as class 0. SVM gives a probability of the label assigned. Can I rank the results of class 1, ...
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0answers
20 views

Suitable Model for predicting flight delays in R [closed]

I want to predict the flight delays.Which classifier or which machine learning algorithm i have to use for predicting the flight delays in R and please guide me how to find the accuracy of that ...
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8 views

Larger Costs and Gammas in SVR

I always thought that larger Costs and Gammas in SVR (epsilon) produce higher complex models (what I know about SVM complexity is based on SVs quantity). Is this right ?
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14 views

Does collinearity of one-hot encoded features matter for SVM and LogReg?

Sometimes I encode categorical features as binary values - one feature per possible category value indicating whether that feature name matches the original category value (i.e. one-of-K scheme). Now ...
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1answer
26 views

Regression with a kernel

I have a fixed kernel and a set of points. I do SVC with the flavor of SVM classification i'm working on (assume it's just a regular SVM) and i obtain a classifier represented by an explicit vector of ...
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10 views

Cherkassky SVR C value

In Cherkassky method, C parameter can be taken by the training targets (mean and standard deviation), in "Practical selection of SVM parameters and noise estimation for SVM regression". my doubt is ...
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1answer
15 views

Cost in e1071's SVM doesn't seems same as svmlight's Cost. How to provide cost for balancing training by imbalanced train dataset?

The manual of e1071 library states the following definition for its cost parameter: ...
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25 views

Why CV in SVR gives me better results with high Costs?

Why CV (5fold) my dataset (15912 samples [0,1] scaled, [9.5-75] target range) keeps giving me lower MSE when growing C ? I can't find a stopping point for reaching good parameters.
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1answer
20 views

LIBSVM: output of svm-predict is all 0 even though I'm using the test data which was used for training

I'm using libsvm to perform binary classification. I used easy.py for training which is included in libsvm library. After running easy.py, it showed the following in stdout. ...
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24 views

SVM fusion training data set

For a binary classification problem, I have split the data set into multiple sets and trained each set using a SVM. I want to combine the outputs from each data set using another SVM. What is the best ...
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1answer
36 views

Differences in scaling values

Every tutorial that I read says it´s important to scale data before training. What is the difference between scaling in ranges [0,1], [-1,1] and [-5,5] ?
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1answer
23 views

Does a polynomial kernel with degree less than 1 satsify mercers condition

Consider the polynomial kernel: $$K(\boldsymbol{x}, \boldsymbol{x}') = (\boldsymbol{x}^{T} \boldsymbol{x}'+c)^{d}$$ This kernel satisfies the mercers theorem/condition. Since I never saw any ...
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54 views

How to validate sentiment classification and compare different algorithms

I need to compare SVM and NB about sentiment classification by evaluating accuracy, precision and recall measures. I have 1500 manually classified documents, and I would know which is the best way to ...
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12 views

Suggestion for method/framework to use for short string classification with “complex” ouput

What I am trying to do : I have short text strings (max 128 total chars in length) which I would like to classify (or use for prediction) as belonging to a particular type of output (more on the ...
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1answer
15 views

The meaning of the output from grid.py in libsvm

I'm a newbie in SVM, and have several questions regarding a tool in libsvm. There's tools/grid.py which tools/README explains as "parameter selection tool for C-SVM classification using 47 the RBF ...
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1answer
56 views

Which hyperplane separates these two classes?

I have a dataset of 3 dimensional points in two classes, I want to separate between the two. As the plot suggests, these two are completely separable but I don't know the formula to form the ...
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22 views

How are ELMs tuning-free?

I have read that Extreme Learning Machines do not need any kind of iterative parameter tuning. However, in the MATLAB implementation of ELM that I use, I have a variable ...
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1answer
14 views

prove that SVM chooses the bisecting line of nearest support vectors?

I have trouble solving the problem 3.18 from "pattern recognition" by "Sergios Theodoridis, ‎Konstantinos Koutroumbas" the problem is : Show that for the case of two linearly separable classes the ...
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16 views

SVMs with some constant and some changing features

I am doing binary classification using SVMs. Some of my features change at certain events in time. At some point they don't change anymore. For tests on my marked dataset I simply look at this state. ...
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4answers
328 views

What makes the Gaussian kernel so magical for PCA, and also in general?

I was reading about kernel PCA (1, 2, 3) with Gaussian and polynomial kernels. How does the Gaussian kernel separate seemingly any sort of nonlinear data exceptionally well? Please give an intuitive ...
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1answer
43 views

One class SVM to detect outliers

My problem is I want to build a one class SVM classifier to identify the nouns/aspects from test file. The training file has list of nouns. The test has list of words. This is what I've done: ...
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1answer
26 views

Does the method of computing feature weights for linear kernel SVM also works for radial Kernel SVM?

I searched for how to find feature weights and found this stackoverflow answer. It gives the following equation to get the weights: ...
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1answer
19 views

Getting less number of features in weight vectors as were provided for SVM

I have trained a SVM with 18881 features and wanted to know the ranking of features. I tried the method given at http://stackoverflow.com/questions/7390173/svm-equations-from-e1071-r-package for it ...
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40 views

Weka LibSVM one class classifier always predicts one class

I'm trying to use LibSVM classifier in Weka to build a one class SVM classifier. My training file has list of noun words. My test file has many words. My aim is to use the classifier to predict the ...
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25 views

Analyzing variance of major parameters of SVM model

I am using SVM to classify a two class problem using the set of features from a dataset of 474 samples making 237 training, 237 test samples. I have cross validated by making 100 random combination of ...
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1answer
27 views

pairwise distances used as features for classification

I have a feature matrix 977x3 features = rand(977,3); where each row is an observation and each column is a feature. I calculate the pairwise distances between ...
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2answers
32 views

SVM and SMO main differences

I am unable to clearly see the main differences between SVM & SMO. While I get the fact that SMO provides better algorithm for QP solvers but I see that when I use this in Weka on my MacBook it ...
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16 views

Is Multi-output of SVM Feasible for my research?

I am working on a decision making system, something about concert prices prediction to maximize the profit. Because it is multi-output, now data mining algorithm I know only neural network is suitable ...
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40 views

Machine learning algorithms for panel data

In this question - Is there a method for constructing decision trees that takes account of structured/hierarchical/multilevel predictors? - they mention a panel data method for trees. Are there ...
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1answer
67 views

SVM RBF performance on “dissimilar” data

I've been studying the performance of machine learning algorithms on "dissimilar" data (that is, prediction on new data that are not that "similar" to the training set) and I came up with this ...
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27 views

The optimization problem of soft margin Support Vector Machine: How to interpret?

I try to understand what exactly we are trying to optimize in the case of Support Vector Machine problem, which supports soft margins. The original problem is posed first as, without soft margins ...
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1answer
57 views

Grid search error in LIBSVM while optimizing C and g parameters

I am using libsvm for a one-class classification problem. I am trying to select the ideal C and gamma parameters for different kernels(polynomial, linear and rbf) I am using the suggested matlab code ...
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1answer
25 views

Distance from hyperplane in SVM rbf kernel in R

I am running ksvm in R(using kernlab package) for a highly imbalanced data.Is there any way i can get the distance of my test data points(each of dimension 8-10) from the hyperplane?so that i can ...
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38 views

One-class SVM vs NN with backprop… Or is there something better?

I'm pretty new to unary classification, so I've been playing around with different approaches to one-class document classification in Python. NN seemed promising at first, but has some undesirable ...
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0answers
25 views

Feature engineering with non-fixed length vectors?

I have a bunch of data that looks like this: ...
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8 views

max margin vs max posterior/likelihood advatages

I am working on some parameter learning approaches for image classification. What is the differences between the following two for image classification? max margin methods maximum likelihood/ ...
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12 views

Profiling high-scoring clusters in a multi-dimensional feature space

I have a large amount of samples, which have a multi-imensional feature vector associated with them. Each sample has a "score", and the length of the feature vector is substantial (n>100, and in ...
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18 views

SVM decision boundary for linearly transformed (strictly positive definite, diagonal) data points

Let the training data given as $ \left\{x_i,y_i\right\}_{i=1}^n $ and let the corresponding optimal max-margin SVM classifier be $ f\left(x\right)=w^Tx$. Let us now apply a strictly positive definite, ...
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1answer
36 views

Check a status of training process in R

I'm training a model using caret package in R for almost 3 days. The calculations are running in parallel (multiple processes). Unfortunately there is no output in ...
3
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0answers
43 views

Explanation for large difference in SVM and Naive bayes results

I have a dataset with 389 data evenly distributed into 6 classes. Each data has 1024 features. So my dimension is much larger than my observation data. I have tried to see some common classifiers on ...
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2answers
80 views

SVM heavily over fits the data (classifying Highly Unbalanced data )

I have a huge training set from which I am supposed to regress and classify, i.e I classify whether an event will occur or not and another task is to regress the intensity of the event in future. The ...
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1answer
22 views

Affect of Misclassification Cost on SVM

I am using Matlab to train an SVM for very unbalanced data. However, my concern is not so much for the particular class assignment (ie 1/0), but rather to the scores (the prethreshold continuous SVM ...
3
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1answer
57 views

SVM: Number of support vectors

Imagine I am using an SVM to train a classifier for a given dataset, in one-vs-all configuration. For each class, I am performing cross validation for parameter selection (grid search to choose ...