Questions tagged [svm]

For questions about Support Vector Machines/Networks.

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Scoring feature vector with Support Vector Machine

I am reading the R-CNN paper by Ross Girshick1 et al. (link) and I fail to understand how they do the inference. This is described in the section 2.2.Test-time Detection in the paper. I quote: At ...
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19 views

Is it possible to combine multiple SVMs that were trained on sublayers of a CNN into one combined SVM?

I have created a CNN for use on the MNIST dataset for now (so I have 10 classes). I have trained SVMs on the sublayers of this trained CNN and wish to combine them into a combined SVM as to give a ...
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41 views

A generalized quadratic loss and Newton iteration for Support Vector Regression, why doesn't it generalize well?

I'm comparing the results of an Newton optimizer for a modified version of SVM ( a generalized quadratic loss, similar to the one stated in: A generalized quadratic loss for SVM ) with classic SVM^...
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1answer
63 views

How do I combine models trained on different data to increase classification accuracy?

I have two trained models. One is using a LinearSVC algorithm and is trained on numerical data from medical examination from patients with diabetic retinopathy. The second one is a neural network ...
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0answers
46 views

Implementation of SVM - theory to practice

I'm studying Support Vector Machines in the machine learning course, I'm a computer scientist, I've quite understood how SVM are designed thanks also to 16. Learning: Support Vector Machines - MIT. ...
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0answers
20 views

why my regression model predict every datapoint to the same value

I am trying to train a SVR but I found that with some combination of features, the trained SVR predict every point in test set to the same value. this problem occurs much more when I use linear kernel ...
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0answers
43 views

Why do we use the word “kernel” in the expression “Gaussian kernel”?

I've heard the expression "Gaussian kernel" in several contexts (e.g. in the kernel trick used in SVM). A Gaussian kernel usually refers to a Gaussian function (that is, a function similar to the ...
10
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4answers
239 views

What are the domains where SVMs are still state-of-the-art?

It seems that deep neural networks and other neural network based models are dominating many current areas like computer vision, object classification, reinforcement learning, etc. Are there domains ...
2
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0answers
24 views

What is the benefit of scaling the hyperparameter C of an SVM?

Please read the following page of the Sklearn documentation. The figure shown there (see below) illustrates why C should be scaled when using a SVM with 'l1' penalty, whereas it shouldn't be scaled ...
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1answer
19 views

The proper AI method for modeling to predict road crashes and safety surrogate measures

I intend to use an AI method for modeling to predict road crashes and safety sorrogate measures. The dependent variables are crash frequency and other measures that are nonnegative integers. The ...
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1answer
49 views

How does an svm work? How does it perform comparisons between malignant and benign tumor

How do Support Vector Machines (SVMs) differentiate between a glass and a bottle or between a malignant and a benign tumor when it dealing with it for the first time? What will be the analysis ...
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2answers
55 views

Parameter gamma in SVM

I want to understand what the gamma parameter does in svm, according to this page. http://scikit-learn.org/stable/auto_examples/svm/plot_rbf_parameters.html Intuitively, the gamma parameter defines ...
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3answers
209 views

What are Support Vector Machines?

What are Support Vector Machines? Is an SVM a kind of a neural network, meaning it has nodes and weights, etc.? What is it best used for? Where I can find information about these?
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1answer
131 views

Why does training an SVM take so long? How can I speed it up?

I'm trying to create and test non-linear SVMs with various kernels (RBF, Sigmoid, Polynomial) in scikit-learn, to create a model which can classify anomalies and benign behaviors. My dataset ...