# Questions tagged [support-vector-machine]

For questions about support vector machines (SVMs), which are supervised learning models with associated learning algorithms that analyze data used for classification and regression analysis.

59 questions
Filter by
Sorted by
Tagged with
8 views

### Can i integrate yolov5 with svm algorithm

I am currently working on an object detection project. I have already done it with yolov5 and svm separately can i integrate both the algorithm together like YOLO for object localization and detection ...
155 views

### How do I poison an SVM with manifold regularization?

I'm working on Adversarial Machine Learning, and have read multiple papers on this topic, some of them are mentioned as follows: Poisoning Attacks on SVMs: https://arxiv.org/pdf/1206.6389.pdf ...
1 vote
17 views

### Why is the Hinge Loss defined this way?

I have a question regarding the Hinge Loss function used for classifiers and in general the "max-margin" types of classifiers, it is defined as $$max(0,1-t*y)$$ where $t$ is the intended ...
14 views

### Why are projected variables in canonical correlation analysis uncorrelated?

Let $x\in R^d$ and $y\in R^e$ be two vectors with covariance and cross-covariance matrices $S_{xx}, S_{yy}, S_{xy}, S_{yx}$. The canonical correlation analysis is based on the projection of $x$ onto ...
17 views

### Can we derive the support vector machines dual formulation without directly using lagrangian duality theory?

Lagrangian duality theory allows us to derive the dual formulation for support vector machines and to show that the primal and the dual solutions are equivalent. My question is: is it possible to ...
142 views

### Machine learning for arranging 2D points

I have a problem wherein I have 2D points in an image that would be associated with a corresponding label/sequence number. For instance following are 4 such examples: As you can see all of them have ...
804 views

### How should we interpret this figure that relates the perceptron criterion and the hinge loss?

I am currently studying the textbook Neural Networks and Deep Learning by Charu C. Aggarwal. Chapter 1.2.1.2 Relationship with Support Vector Machines says the following: The perceptron criterion is ...
16 views

### Meaning of Objective and Risk in DLIB HOG-SVM detector

I am using dlib simple object detector for training a HOG-SVM object detector. Everything is working fine when I test manually. However, I can't find any resources that tell me what is the meaning of ...
16 views

### My text classifier behaves like regex

I'm trying to train binary classifier that classifies ask to ask programming questions, programming questions that say "I'm getting an error about x/I have problem about x" but don't say the ...
16 views

### Intuition behind replacing constraint in equation for Optimal Separating Hyperplane

I am reading "Optimal Separating Hyperplane" section of the book - Elements of Statistical Learning which is described on page 132 as follows: My questions: The constraint $||\beta|| = 1$ ...
19 views

1 vote
170 views

953 views

### Which kind of data does sigmoid kernel performance well?

While I was playing with some hyperparameters, I came to a wired situation. My dataset is IRIS dataset to be specific. SVM algorithm has some hyperparameters that we can tune, such as Kernels, and C ...
1 vote
66 views

### Why is the accuracy of my model very low on a separate dataset from the training and test datasets?

I am working on stock price prediction project, I am using the support vector regression (SVR) model for it. As I am splitting my data into train and test, I am getting high accuracy while predicting ...