# Questions tagged [svm]

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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### Vectorised Implementation of SVM Gradient

I am trying to implement the SVM loss and gradient. The loss is given as $$L(w) = \sum_{i=1}^N max\{1-y_iw^tx_i, 0 \} + \lambda ||w^2||_2^2$$ I believe that for the loss, this is a good implementation;...
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### Why is One Class SVM predicting that half my dataset consists of outliers?

I am currently working on a dataset with 14 continuous features, a categorical target over five classes, and 90,000 samples. My current goal is to explore outliers in the dataset, and to that end I ...
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### Plot of Decision Boundaries intuition for different SVMs

I have a class imbalanced dataset and I used two different SVMs for binary classification. One plain SVM and one class weighted(i overweighted the positive class). Below are the decision regions I ...
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### How can I write dual problem for the given little dataset and kernel function? Then how can I write kernel matrix(inner product)? [closed]

Actually I know implementation of this problem on code, however I cannot solve it through mathematically, could anyone help me to solve this little problem? I need to get sense about dual problem ...
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### Why minimizing the ||w|| penalty term in SVM definition makes the overfitting less probable?

I understand overfitting and why we want our classifier to be reasonably simple. If we introduce more complexity to the predictor, we are risking that we fit it too closely to data, thus overfit, and ...
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### Representer Theorem for Support Vector Regression

I would like to know what is the expression of the predictor function in terms of the Representer Theorem in the case of Support Vector Regression. For example, in the SVM binary classification case, ...
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### High training and testing accuracy when training a binary classification model

I have a dataset where I split the train/test set to 66%/33%. I noticed my training accuracy is very high (in the 99s) regardless of which classification model algorithm. I also noticed while making ...
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### Non-negative Constraints in Soft-Margin SVM Lagrange Equation

I was reading the A Tutorial on Support Vector Machines for Pattern Recognition as a supplemental for my Intro to ML class and I wasn't sure why $a_i \geq 0$ and $\lambda_i \geq 0$ cannot be ...
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### SVM loss function

I am going through Bishop's book and especially SVM. I am trying to understand the logic behind minimizing the specific loss $argmax_{\mathbf{w}} \frac{1}{2}||\mathbf{w}||^{2}$. On page 327, in 7.3 we ...
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### How to manually calculate predictions of kernlabs SVM

I am trying to manually replicate the predictions of kernlabs SVM (polynomial & radial kernel) using caret. Here is the code to fit the model: ...
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### SVM Model: What's a healthy number of support vectors?

For a SVM model what is a healthy number of support vectors? or more precisely what's a good ratio of number of support vectors to the total number of training samples, 10%, 20%, 30%, 50% ... 80%? Is ...
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### Why minimize radius in support vector clustering

I have recently started studying machine learning on my own. I am reading support vector machines and then support vector clustering. https://papers.nips.cc/paper/2000/file/...
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### Are radial basis kernels able to model interactions between predictors?

I have been doing research using Support Vector Regression for some time, especially using radial basis kernel, for predicting a response variable from a set of numeric predictors. As a consequence of ...
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### SVM: Would we care about the functional margin if maximizing only with geometric margin were convex?

I am reading Andrew Ng's SVM notes (https://see.stanford.edu/materials/aimlcs229/cs229-notes3.pdf) and am lacking the intuition for why we need the functional margin. As far as I understand we need it ...
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### How support vectors is calculated on SVM example?

Question: If we map input data with following $\phi$ function to higher dimension via Hard Margin SVM then support vectors are $a$ and $b$. How we can find support vectors of this example, i.e: ...
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### What's the speed bottleneck in sklearn.svm.SVC.predict?

I'm working with some high resolution images of specimens in test tubes and I found that using an SVC to classify each pixel by HSV value helps me to a great job at segmenting out just the specimen ...
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### AUC plot from a MLSeq::classify object

I have generated a classify object using the MLSeq::classify function. I wonder how I can visualise this using a ROC or AUC curve with sensitivity and specificity on the axis. ...
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### How to find 95% CI of a matrix of classification data?

I am running some support vector machine (SVM) analysis. I can run the analysis and even plot the obtained hyperplane, with methods similar to what is reported here. Essentially, I create a large ...
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### What is the way to compare SVM output?

How can I rigorously compare the results from SVM? I have a feature matrix that contains ~1000 features and the label is either 1 or 0. The features can be grouped into 4 categories, let's say they ...
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### What's the best strategy to fill NAs for a predictor in supervised learning e.g. SVM?

What's the best strategy to fill NAs for a predictor in supervised learning e.g. SVM? I have monthly data for all other predictors since 1963 and for one predictor I have data since 1990 only. So I ...
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### Training/test splits (Monte Carlo sensitivity analysis) or Cross-validation

I am using SVM in Matlab (fitcsvm function) to train a classifier for a problem with two classes. Further, I have three features, e.g. A1, A2 and A3, available for each observation composing my full ...
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### SVM classification metrics are all 1 although there are mistakes in classification

Here is a fitted LinearSVC model showing the learned separating hyperplane for my training samples: And when I use ...
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### How to determine equation of hyperplane for SVM?

Assume we have only two features in our training dataset that is already classified into class C1 and class C2. The transposes of the feature vectors are given below for each class: C1: [2 6], [1 1], [...
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### SVM predicts always the same class

I have a dataset with tf-idf values and their corresponding classes and I am trying to do predictions using SVM. The problem is that all the results that it produces have the same class. Most related ...
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### Testing for causality with Support Vector Machines

Can a support vector machine (SVM) be used to test for causality between 2 or more variables? I know that the original purpose for SVM is classification. I also know that there is a variation of the ...
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### Hard-margin SVM and logistic regression for non-linearly separable data

Hard-margin SVM doesn't seem to work on non-linearly separable data. It seems to only work if your data is linearly separable. What happens if you try to use hard-margin SVM? Does the algorithm blow-...