Questions tagged [svm]

Support Vector Machines (SVM) are a popular supervised machine learning algorithm that can be used for classification or regression.

0
votes
0answers
13 views

Regularization loss - Why is that important to get unique weights solution

There's something that is bothering me in Regularization. There is one bug with the loss function when I just use for e.g. a multi-class SVM loss. Suppose that we have a dataset and a set of ...
1
vote
0answers
14 views

What is the best reference for multi-class SVM?

Can someone suggest some papers about the multi-classification methods by SVM? One against all? A good survey or paper which ...
0
votes
0answers
16 views

Can we use kernel trick in primal problems?

I am wondering if we can use kernel tricks in primal problems in SVM? Without using dot product in dual problem? Also, I am wondering if we have additional constraints. Is there any paper or book ...
1
vote
1answer
16 views

How are Lagrangian multipliers zero except for support vectors in dual representation of SVM?

How can we conclude that the Lagrangian multipliers are zero, except support vectors, in a dual problem? I cannot seem to see it. $$L(\alpha)=-\frac{1}{2}\sum_i \sum_j \alpha_i \alpha_j y_i y_j x_i' ...
2
votes
2answers
31 views

SVM behavior when regularization parameter equals 0

I read on this Wikipedia page the following about soft-margin SVM: "The parameter $λ$ determines the trade-off between increasing the margin size and ensuring that the $x_i$ lie on the correct ...
0
votes
0answers
4 views

Why kernel perceptron relies more on the training data than kernel SVM?

In UCSD machine learning course, it is said that: "for Kernel Perceptron, the solution is likely to depend on more of the training points than the ...
0
votes
0answers
16 views

How to create own dataset for SVM+HOG image classifier for custom character recognition [closed]

I am completely new to the field of machine learning and I am working on a project which requires me to recognize custom characters drawn by the user. The custom character resembles the shape of a ...
1
vote
0answers
20 views

Implementing SVM with Gaussian Kernel

This is referencing Prof. Andrew Ng's course on machine learning. In the part that details implementing an SVM with the Gaussian kernel, we are supposed to use all the training examples as our ...
0
votes
0answers
15 views

Learning curves for active learning regression

I'm applying a query-by-committee active learning algorithm to a regression task using SVMs and I would like to produce the learning curves for comparison with a baseline/passive/random learner. The ...
1
vote
1answer
23 views

Confusion regarding the Working mechanism of Activation function

For binary classification irrespective of the model used, the sigmoid function is a good choice for output layer because the actual output value ‘Y’ is either 0 or 1 so it makes sense for predicted ...
0
votes
0answers
12 views

Is there a non-linear implementation of SP-SVM?

I was trying to implement a parallel non-linear SVM in Python and I found this paper that has a review of different SVM implementations run across CPUs and GPUs and they mention they are focused on ...
0
votes
0answers
7 views

Should detection times get longer for dlib.train_simple_object_detector when I add more images?

I've played around some with dlib.train_simple_object_detector and have found that as I add more images the detection time grows longer when I later perform detections. Why is this happening? To my ...
1
vote
1answer
29 views

Get how similarity between the training data and the income data?

I'am trying to use Clustering and Classification methods as SVM using scikitlearn. I'm also studying some outliers/novelty detections I want something like a semi-supervised model. I want to predict ...
0
votes
1answer
16 views

SVM hyperplane equations for linearly seperable data

I'm going through Wikipedia article on SVM and came across these equations: It says: With a normalized or standardized dataset, the parallel hyperplanes to our required hyperplane $wx+b=0$, can ...
1
vote
0answers
16 views

feature extraction for Radio signals classification

I found some code where the developer is trying to solve the problem of "Radio signals modulation classification" in this link link one of the solutions is using SVM to solve the classification ...
0
votes
0answers
12 views

Formulation of Optimization Problem in SVM

I need help in verifying/understanding a step in formulating an optimization problem used for support vector machines (though this question doesn't need any background in SVM). Consider a bunch of $m$ ...
2
votes
2answers
86 views

Interpretation of ROC AUC score

i tried to evaluate 6 models and after plotting , this what i get : So i'm wondering , if those results are "Right" ? Thank's in advance.
5
votes
1answer
66 views

Is there any conceptual relationship between 'kernel' in SVM and 'kernel' in convolution neural net?

In SVM, we have kernel function that maps an input raw data space into a higher dimensional feature space In CNN, we also have a 'kernel' mask that travels the input raw data space (image as a matrix)...
0
votes
0answers
14 views

Does one hot encoding in svm for nominal training set gets done by the weka package and package or library particular for svm by itself?

While using svm in java (weka) with nominal input set, does the inbuilt algorithm itself does the one-hot encoding or is it required by the user to do so?
0
votes
1answer
22 views

What do each of the three SVM classes in R represent?

Inspired by this post, I took a look at this doc SVN in R output this: ...
3
votes
1answer
68 views

What are the differences between SVC, NuSVC, and LinearSVC?

What are the differences between SVC, NuSVC, and LinearSVC? Please shed some light.
3
votes
1answer
28 views

Hinge Loss understanding and proof

I hope this doesn't come off as a silly question, but I am looking at SVMs and in principle I understand how they work. The idea is to maximize the margin between different classes of point (within ...
0
votes
0answers
8 views

Normalization in SVM classifier

I am trying to normalize my features for a classification model with 3 class outputs. There are two kinds of features. First is medical test results and second is patient information such as age. The ...
0
votes
0answers
14 views

SVM classifer gives the same output for all test cases

I have a dataset belonging to seven different classes. Each input consists of 1024 features. There are only 30 samples belonging to each class available for training. I have used several ...
0
votes
1answer
32 views

How is hinge loss related to primal form / dual form of SVM

I'm learning SVM and many classic tutorials talk about the formulation of SVM problem as a convex optimization problem: i.e. We have the objective function with slack variables and subject to ...
0
votes
0answers
14 views

Theoretical supremacy of Gaussian SVM

Many packages such as sklearn use RBF kernel as default for SVM classification. I wonder if there is a proof/explanation why this is the "best" (I am aware of the no free launch theorem) kernel for a ...
0
votes
1answer
18 views

How many features can we input for a SVM to classify?

I am new to SVM classifiers. I read on the internet that SVM are binary classifiers and also many SVMs, as described in research papers, only take 2 features as the input. (e.g. https://scikit-learn....
1
vote
1answer
37 views

Soft SVM solving for $b$

I don't really understand how to approach this problem. I know that $w=\sum_{n=1}^{N}{a_ny_nx_n}$ and $y_n(w^T\cdot x_n+b)=1. $ So I can solve for $b$ from that equation but I can't figure out how to ...
1
vote
0answers
36 views

SVM/Naive Bayesian text classification on multiple features

I was building a text classifier which takes into account certain features of the text and classifies them into two - "Yes" or "No". I have trimmed the text, removed stopwords and have applied TFIDF ...
1
vote
0answers
14 views

Isolated/noisy instances that have outsized effect on SVM hyperplane selection

Consider two linearly separable classes and the optimal separating hyperplane (image credit Prof Jiawei Han of UIUC): Now consider if there were a single "rogue" point for the Yellow class - which ...
0
votes
0answers
7 views

How to choose parameters for OneClass SVM? [duplicate]

I would like to know how can I fix my OneClass SVM classifier parameters "gamma & mu" to get a better precision? Is there any relation between my data classes and the parameter's value? Thanks in ...
0
votes
2answers
68 views

Smaller test data set than training data set in machine learning

I would like to train different machine learning algorithms (SVM, Random Forest, CNN etc.) for the same data set (e.g. MNIST) und then compare their accuracies. The goal would be to find out from ...
0
votes
0answers
20 views

Combine AdaBoost and Support Vector Regression?

I have read several papers about using SVM instead of decision tree in AdaBoost, but I haven't seen any papers about using support vector regression (SVR) in AdaBoost. However, if using support vector ...
5
votes
3answers
129 views

Looking for a classification (?) algorithm for linearly separable but unlabeled data points

I have a dataset that is linearly separable with two lines - something like that: Now I'am looking for the right kind of algorithm to do what I guess a SVM would do with labeled data - find the ...
0
votes
0answers
28 views

New images always predict one label

I have trained a SVM for image classification using RGB histogram as features and a couple of other ones. These are my feature and label sizes: ...
0
votes
1answer
31 views

Having averaged trials which are less than the number of features

Suppose I have an experiment where I have 70 features and 48 samples. The target variable is binary (0,1) and the 48 samples are divided such that 24 of them correspond to outcome 1 and the other 24 ...
1
vote
3answers
61 views

Why did Logistic regression perform better than svm? [closed]

I have a data set of movies and their subtitles.My task is to classify them based on their ratings-[R,NR,PG,PG-13,G]. I have tried different ML algorithms and found that Logistic regression out ...
1
vote
1answer
36 views

Tuning C hyper parameter in Soft Margin SVM in Matlab

How to tune the C 'BoxConstraint' hyperparameter in soft margin SVM to get the best optimal value?
0
votes
0answers
19 views

Hard margin SVM in Matlab

How can I build a hard margin svm model using matlab builtin functions such as fitcsvm and fitclinear? Should I set the ...
1
vote
0answers
47 views

SVM hard and soft margins in matlab,

I am comparing the performances of several SVM models in matlab using the fitcsvm function, and I want to double check that I am using the correct syntax for hard ...
0
votes
0answers
77 views

SVM hyperparameters using Matlab's fitcsvm and OptimizeHyperparameters

I am building SVM models and will compare their performances, linear vs RBF, and I'm using OptimizeHyperparameters to get best hyperparameters C (BoxConstraints) ...
1
vote
1answer
108 views

SVM with Tensorflow

I have an array of Numpy with the following data, for example: ...
2
votes
1answer
33 views

An ambiguity in SVM equations about misclassified data

I have encountered an ambiguity in SVM equations. As is stated in Chris Bishop's machine learning book, the optimization goal in SVM is to maximize this function: $$C\sum\limits_{n = 1}^N {{\xi _n}} ...
2
votes
2answers
83 views

Setting best SVM hyper parameters

I have a non linear data set, and I am using SVM (RBF kernel) to build a classification model, but not sure how to set the best hyperparameters of the SVM, C and gamma in Matlab ...
0
votes
1answer
87 views

Implementing SVM from scratch?

I am trying to implement the rbf kernel for SVM from scratch as practice for my coming interviews. I attempted to use cvxopt to solve the optimization problem. However, when I compute the accuracy and ...
0
votes
1answer
15 views

When to question output of model

I'm unsure of how to ask a question without making it seem like a code review question. At what point does one question whether they've actually implemented the algorithm and-or model correctly? ...
0
votes
1answer
21 views

What is the possible range of SVR parameters range?

I'm working on a regression problem. While tunning the Parameters of SVR I got the following values c=100, gamma= 10 and epsilon =100. For which I got 95 percent r-square. My question is what is the ...
1
vote
0answers
20 views

Hyperparameter Tuning with Simulated Data

I'm trying to create a SVM classifier which can predict some fault, and to train it I'm using simulated examples of the fault. Of course, the simulations are not perfect, but they appear to be good ...
2
votes
3answers
52 views

Are support vector machines and logistic regression equivalent if data is linearly separable?

I understand that SVMs separate data drawing an hyperplane with the biggest margin, but doesn't logistic regression do the same thing if data is linearly separable?
3
votes
3answers
64 views

How to set hyperparameters in SVM classification

I am studying image classification using SVMs and it is generally defined as so... N = number of training examples W = is the weights f(x, W) = dot product λ is explained to be set through cross-...