SVM Vs Neural Network Vs Random Forest classifier comparison on multi class...
Any idea if SVM or Neural Net or Random Forest works better on a classification problem on the same multi class dataset? I mean, in general, which should outperform the comparison?
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Modeling with Support Vector Regression (SVR) [closed]
I’ve created a model with SVR and using this csv file as training and test data. I’ve tried following python code snippet but I’m not sure either the model is working or my plots are correct!? import...
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What is the purpose of +1/-1 constraint on SVMs
It is common knowledge that all SVMS try to optimize some permutation of the following equation with the provided constraints: however, my question lies on the purpose of the constraint >= 1 and...
View ArticleLSSVM Prediction using LS-SVMLab toolbox v1.8
I’m trying to forecast a time series of air passengers using LSSVM with the help of the LS-SVMLab toolbox v1.8 from http://www.esat.kuleuven.be/sista/lssvmlab/, specifically the NARX model function. I...
View ArticleConfused Scikit results
I am doing classification machine learning on a particular dataset on which an SVM model (using Scikit.learn) is giving a Matthew’s correlation coefficient (MCC) of 0.50, whereas random forest and KNN...
View ArticleHow different is Support Vector Regression comapred to SVM?
I know the basics about SVM and SVR, but still I don’t get how the problem of finding a hyperplane which maximizes the margin fits into SVR. Second, I read something about $epsilon$ used as margin of...
View ArticleBinary linear support vector machine classifier
I am trying to classify between two different categories a set of 2 dimensional points with a linear SVC. To train the model I use a dataset with 64 samples from class A and 230 from class B. Is this...
View ArticleMaximum Margin Clustering on Unit Hyperspherical Data
So I was working on the following problem Given a set of points $Q$ in $mathbb{R}^n$ on the unit hypersphere $x_1^2 + … +x_n^2 = 1$ and the guarantee that there exists a hyperplane $c_1x_1 … c_n x_n =...
View ArticleSVM kernels combination
Let’s suppose we have classification problem with two classes. $$X^l = (x_i, y_i)_{i=1}^l, Y={+1, -1};; y:Xrightarrow Y$$ $$x_i in R^n, y_i = y(x_i),;; i = 1dots n$$ One of the most spread methods to...
View ArticleLS-SVM time series forecasting
I’m trying to forecast a time series of air passengers using LSSVM with the help of the LS-SVMLab toolbox v1.8 from http://www.esat.kuleuven.be/sista/lssvmlab/, specifically the NARX model function....
View ArticleCalibration of SVM Probability
I am using 2-class SVM from e1071 R-Package. I have been recommended to calibrate the output of classifier. In this regard, I found this page. The code works for me and I want to apply it in my...
View ArticleA simple question about cross-validation [duplicate]
This question already has an answer here: How does leave-one-out cross-validation work? How to select the final model out of $n$ different models? 1 answer
View ArticleMulticlass SVM result
I have a problem with multiclass SVM result. My classes are {-1,0,1} and my CVed precision is {0.2,0.8,0.8}, where contribute with -1 poor classification. If I change classnames to {6,5,4} my CVed...
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“Good” classifier destroyed my Precision-Recall curve. What happened?
I’m working with imbalanced data, where there are about 40 class=0 cases for every class=1. I can reasonably discriminate between the classes using individual features, and training a naive Bayes and...
View ArticleBlame SVM features for misclassifications
I am classifying webpages based on several features of HTML-structure. I get the best cross-validation results with the RBF-kernel. With a linear kernel, if I understand correctly, it is possible to...
View ArticleHow to use sklearn Pipeline with custom Features? [on hold]
I am doing text classification using Python and sklearn. I have some custom Features which I use in addition to vectorizers. I would like to know whether it is possible to use them with sklearn...
View ArticleThe whole procedure of training (using LOO-CV) and testing SVM classifier
I have two separated data for training and testing. I would like to make a SVM model using Leave-One-Out (LOO) cross-validation(CV). The procedure I follow is like the below pseudo code: n.tr <-...
View ArticleUsing sklearn.svm.SVC for binary classification and getting 0% accuracy!
I am using the default SVC with rbf kernel to do a leave one out procedure for training and predicting, i.e. I am leaving one sample out at a time for both X and y and using the rest of the samples to...
View ArticleHow to assess text classification results when extreme sparsity is present?
I try to classify documents based on bag-of-words single word approach. I employ R with its RTextTools to use SVM. My text files are like below: TRAIN Text,Label nalyt appropri boundari boundedspac...
View ArticleMulticlass classification one versus one with ensemble
If I use an ensemble, which consists of four classifiers, in order to classify my data into three classes. Further, suppose I use the one versus one strategy. My question is: How to fuse the...
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