Tweaking SVM error rates?
I currently have a one-vs-all SVM setup. Each SVM outputs a score. If I take the maximum score as the correct corresponding class, this gives me FARs of 0.008%. However it also gives me FRRs of about...
View ArticleCan we compare classifier scores in one-vs-all/one-vs-many?
In a system where we perform multi-class classification via a one-vs-all technique, are two scores comparable? E.g.: If I have 0.5 and 0.6 on two different classifiers, is it possible to say that the...
View ArticleOverfitting in One-Class SVM
In a one-class SVM model, would a low value of $nu$ be considered over-fitting the model or would a large value of $nu$ be considered over-fitting? I’m very confused as, in the latter case, as $nu...
View ArticleNon-probabilistic vs probabilistic frameworks for decision theory in metric...
I have a task to make a decision, say to classify an object as $X$ or $ overline X$. However, $overline X$ usually means everything else and you only have positive examples of $X$ and not so many...
View ArticleAre there kernel-based one-class sparse kernel-based outlier detection...
I have a commercial outlier detection problem in moderate dimension (8-25). We have a limited number of true positive tags and can roughly evaluate performance of various methods. So far, the 1-class...
View ArticleAccuracy on the test set do not change. Why?
I train a SVM classifier using 36 features. If I use all the features, the train accuracy is about 0.96, the test accuracy is about 0.77. Then I change the number of features. The train accuracy drops...
View ArticleWhat is the difference between Machine Learning and Deep Learning?
OK, I know there is a lot of topic regarding this in the internet, and trust me, I’ve googled it. But things are getting more and more confused for me. From my understanding, Deep Learning (DL) is kind...
View Articlee1071: CVE returns linear separation, Hold-out returns large error
I’m using the Adult dataset that can be found here: http://archive.ics.uci.edu/ml/datasets/Adult After taking a sample of the dataset, I use the svm function of e1071 to obtain the accuracy with a...
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...
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 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 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 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 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...
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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 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...
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 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 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 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...
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