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 we boosting or stacking with different input variables for each model in machine learning?

I have a question about Boosting and stacking in machine learning. Suppose that I will train neural network, SVM and logistic regression using optimization algorithm to optimize best inputs in first ...
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How do I evaluate the accuracy in estimating a set?

Say I have a training set $D$ of only positive examples, from which I learn a set $A$ such that $D \subseteq A$, and $A$ needs to be the "full" set -- i.e. I try from a small set generalize to a ...
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56 views

How to transform categorical variable into numerical variable when using SVM or Neural Network

To use SVM or Neural Network it needs to transform categorical variables into numeric variables, the normal method in this case is to use 0-1 binary values with the k-th categorical value transformed ...
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34 views

Support Vector Machines and the curse of dimensionality

I am reading this paper: "Automated MR image classification in temporal lobe epilepsy", by Focke et al. NeuroImage, 2012. The authors use support vector machines to classify subjects between healthy ...
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15 views

Does centering or mean normalizaiton alone every help in feature scaling?

In feature scaling, one way is to subtract the mean (centering) and then divide by the standard deviation for all data points. Suppose we just centered the data and didn't divide by the standard ...
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24 views

Classifying arrhythmia using SVM on Matlab [closed]

I am doing my graduation project QRS complex detection (using DWT) and arrhythmia classification (using SVM) in Matlab. I have found features of the ECG signal includes R peak detection, QRS complex, ...
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22 views

Correct arguments for svm() function in R

I'm looking to implement a linear and non-linear SVM in R but having some confusion over which argument to use in svm(). For the linear SVM I want to add in the penalty $\gamma$ for soft margin. This ...
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15 views

Multivariate Non-parametric Regression

What is the most well known(or most effective) method for multivariate nonparametric regression? I am surprised that there is no 'popular' support vector machines' based method.
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13 views

Mean Average Precision in Matlab with liblinear and vlfeat

I want to find the mean average precision (meanAP) from a classification problem. I am using liblinear for classification and I am trying to use vlfeat for the precision because it already includes a ...
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256 views

Why doesn't a non-linear kernel improve accuracy in high dimensions compared to a linear kernel?

I read somewhere that if the number of dimensions in your feature set is very high, then a non-linear kernel such as RBF (or any other) may not help in increasing accuracy compared to a linear kernel. ...
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17 views

Tune function in R for SVM tune.svm() scale data?

I have been trying to use SVMs for a while under R but I have very big troubles to find informations about those functions. For instance, you can read that the svm() function from the e1071 does ...
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16 views

Which one to choose and when? One-v/s-One and One-v/s-All classification for multi-class classification

In case of multi class classification task, how do we decide which among the two options viz. one-v/s-all and one-v/s-one do we choose for model building? Is there some criterion based on which we ...
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19 views

Cross-validation ($3$-fold) for optimizing ($C$, $\gamma$) in RBF-SVM

Let $\mathcal{X}$ be a training set which will feed a binary SVM with RBF kernel. $\mathcal{X}$ consists of $10$ positive examples and $100$ negative examples. I am interested in optimizing the ...
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51 views

Time series forecasting using Support Vector Machines

I have been trying to use Support Vector Machine method for time series forecasting. I have seen allot of research papers, but nobody shared the code or tool they have used for that. Got some ...
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9 views

ensemble model for SVM

I did a nested 5-cv and the resulting models are unstable (high variance among the hyper parameters C and gamma of SVM). So, I don't know how to choose C and gamma for the "final" model. I read that, ...
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25 views

Why does Support Vector Regression slow down after several iterations?

TLDR: Why does SVR slow down on my machine after multiple runs in IPython/sklearn? I'm trying to grid-search to optimize some parameters in Support Vector Regression with a problem that has 2 ...
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42 views

how does a linear svm classifer work

I have been checking about SVMs in particular linear SVMs throughout many questions here. However, one problem i faced is that there seems to be no indepth explanation on how does linear SVM works in ...
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13 views

Getting probability of each new observation being an outlier when using scikit-learn OneClassSVM

I'm new to scikit-learn, and SVM methods in general. I've got my data set working well with scikit-learn OneClassSVM in order to detect outliers; I train the OneClassSVM using observation all of which ...
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19 views

SVM for an unbalanced textual dataset?

I have a text classification task, currently I can classify the data with very poor precision. This are the scores: ...
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31 views

Unsupervised learning outlier detection

I have a dataset that looks as follows userid⇥week1⇥week2 ⇥week3⇥week4⇥week5⇥week6⇥week7 ...
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12 views

To interpret SVM's probability output in text analysis

So, my question is about the application of the SVM's (or naive Bayes') probability output (via Platt's scaling). I know the interpretation of the output is the probability of a given observation ...
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15 views

How to tune parameters of SVM Rank?

I am using SVM Rank, which has multiple parameters, changing whom I am getting a variety of results. Is there some mechanism to tune and get the best parameters? Below are the different parameters: ...
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30 views

Classification of time series with SVM

Background: I'm currently trying to find interesting anomalous interferences in time series data. I have quite large database of collected data with many different measurements (over 2k measurements ...
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31 views

What do these decision boundaries indicate in random forest and svm?

I was working on data science harvard homework problem. It is a two class classification problem in which they plot the decision boundary for random forest, svm and decision tree. The problem has 2 ...
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19 views

SVM In text classifcation

I am learning about SVM in text classification. However, here i am posed with a problem. I have a dataset of documents which have 3 class labels. First Question Do i split the dataset into ...
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26 views

SVM Classifier: proper process

I'm working on a classification system of mine, but am needing help with the proper process order. Specifically, I'm using LibSVM and a range of feature sets extracted from my data. I'm wondering, ...
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Asymmetric cost assignment for SVM [migrated]

I need to assign different costs based on error: • False negative – 10 • False positive – 1 ...
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23 views

Is the solution of SVM classifier a vector in second conjugate space of the RKHS

Let the training points be given by $x_1, x_2 \cdots x_m$. Suppose we want to predict the class of a new point $x$ as $f(x)$. In an linear SVM this is a dot product usually denoted by $<w,x>$ ...
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28 views

Regularizing the dual variables in SVM

Consider the the optimization program of the kernelized SVM: $$\text{maximize}_{\alpha} ~~ \alpha^T1-\alpha^TQ\alpha$$ $$\text{subject to:} \sum_{i=1}^N \alpha_iy_i=0,~0\leq \alpha_i\leq c$$ where ...
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30 views

LDA vs. SVM for Dimensionality Reduction

Whats the difference between LDA and Linear SVM for dimensionality reduction. I am little confuse as LDA also looks for projection that separates the classes of data and SVM we also look for ...
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What is a good goal for a 5CV in SVR?

I'm running into a complexity x accuracy problem. For example, in a 5CV working with an Epsilon-SVR: ...
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Class densities w/ SVM (LibSVM)

I have a question regarding number of class samples for training and testing with an SVM. For my situation, my training and testing samples both have the same number of class 1 and class 2 ...
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40 views

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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10 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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41 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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23 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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27 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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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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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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11 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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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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30 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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14 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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31 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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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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47 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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33 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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44 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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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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66 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 ...