Questions tagged [svm]

Question 1

I am listening to a lecture on soft margin SVM https://youtu.be/XUj5JbQihlU?si=b66SblRnw9mmczVU&t=2969 The lecturer says that the blue dot represents a violation of the margin. I don't really ...

Question 2

It is widely known that if you were to calculate the maximizer of the dual SVM program (denote as $\alpha^*$), then the primal minimizer of the hard-margin SVM program, \begin{aligned}&{\underset {...

Question 3

I trained a SVM multiple regression model and want to know how much each feature contributes to the prediction variance (quantified by the RMSE). I got the Shapley values for each feature on data from ...

Question 4

I have trained a multiregression model using non-linear SVM, and got quite good metrics, with no big differences between test (20% data) and train (80% data) metrics. The following are the test/train ...

Question 5

I am trying to figure out how to infer C in support vector machine. C is the upper bound on magnitude of lagrange multipliers. These multipliers are not independent. They are probably mutually ...

Question 6

Memorability scores for a set of words can be downloaded from here. I am interested in seeing how well semantic embeddings can predict the relative memorability of words, as measured by Spearman's rho....

Question 7

How would a visualization of the data underlying SVR, such as in svm(X,y,type="nu-regression",kernel="linear",nu=0.5) look like in 3 dimensions (...

Question 8

I'm trying to build an SVM model using the ksvm function from the kernlab package in R. My dataset is about breast cancer, and I'm trying to predict the diagnosis variable, which is a factor. All the ...

Question 9

I have two classes of data to train a linear support vector machine. To be specific, I used Principle Component Analysis to project the data to 2-dimension and trained the support vector machine. I ...

Question 10

I'm encountering a multiclass classification problem where I'm trying to predict 4 categories using SVM. I'm trying to fine-tuning its hyperparameter using Bayesian Optimization to speed up the ...

Question 11

Problem Description: In a manufacturing plant, products are inspected for defects. Each product can have zero, one, or multiple types of defects present. Each defect type belongs to one of three ...

Question 12

In soft-margin SVM in its kernelized form the objective is $$ \min_{\alpha \in \mathbb{R}^n} \biggl[ \tfrac{1}{2} \sum_{i=1}^n \sum_{j=1}^n \alpha_i\,\alpha_j\,k(x_i, x_j) \;+\; C \sum_{i=1}^n \max\...

Question 13

I recently conducted a Principal Component Analysis (PCA) on a dataset with a four-category target variable. While the PCA score plot revealed excellent separation for one group, the remaining three ...

Question 14

I'm trying to build 1D-CSVM model which is a model for pixel-vise classification (aka way of segmentation) of hyperspectral images and is a combination of CSVM and 1D-CNN . In section D....

Question 15

Why in most explanations of the kernel trick is Mercer's Theorem used as justification? Can we not justify it as well with Moore-Aronszajn, which does not place the assumption of compactness on $X$ ...

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Questions tagged [svm]

Is the figure showing margin violation for the support vector machine correct?

Is the strong duality of the hard-margin SVM really trivially satisfied all the time?

Interpreting Shapley values for variance decomposition?

Estimating the contribution of each feature to regression model prediction variance

What's the distribution of the lagrange multipliers found by quadratic programming? [closed]

SVR model is learning rather too well

How to visualize Support Vector Regression in 3d

Unrealistically high accuracy (100%) with ksvm model from kernlab in R

Compare performance of support vector machine after feature deletion [closed]

Best way to tackling SVM fine-tuning

How to Model a Multi-Label, Multi-Class Classification Problem for Defect Detection in Manufacturing?

How to show kernel SVM solutions are sparse using the Representer Theorem (without directly invoking KKT)?

High Classification Accuracy Despite Poor Separation in PCA for Multi-class Data

How to get result mask from 1D-CSVM model?

Why Mercer's Theorem is always cited for kernel learning and not Moore-Aronszajn

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