# Tagged Questions

2answers
181 views

### Linear kernel and non-linear kernel for support vector machine?

When using support vector machine, are there any guidelines on choosing linear kernel vs. nonlinear kernel, like RBF? I once heard that non-linear kernel tends not to perform well once the number of ...
1answer
63 views

### Relationship between the kernel and the value of C in SVM's

How exactly does the value of C relate across different kernels that we can use for SVM's? As in, how does it vary when changing the polynomial degree of a kernel or while using a Gaussian kernel?
0answers
48 views

### Where does the square root for a polynomial kernel mapping function come from?

I'm trying to understand how polynomial kernel functions work, in my textbook it shows an example with a degree of 2, with an input dimension of 2: $K(\vec{x}, \vec{y})$ = $(1 + x_1y_1 + x_2y_2)^2$ ...
0answers
24 views

### SVM kernel mapping, finding boundaries in projected space

I have a question about the support vector machine (SVM) kernel trick. How do you find the boundaries of the training data set in kernel projected space? Is that the same boundaries as you can obtain ...
0answers
105 views

### I am still confused with Gaussian kernel in SVM

From the slides http://www.csie.ntu.edu.tw/~cjlin/talks/kuleuven_svm.pdf, $$\min \frac{1}{2}w^Tw$$ subject to $$y_i(w^T\phi(x_i)+b)\ge 1,i=1,\cdots,n$$ I think most people are very familiar with ...
2answers
231 views

### The Gaussian kernel

In SVM, the Gaussian kernel is defined as: $$K(x,y)=\exp\left({-\frac{\|x-y\|_2^2}{2\sigma^2}}\right)=\phi(x)^T\phi(y)$$ where $x, y\in \mathbb{R^n}$. I do not know the explicit equation of $\phi$. I ...
1answer
91 views

### Trouble with kernel in kernlab R package

I'm using kernlab package Here are two examples: First: ...
0answers
90 views

### Generalized RBF Kernels

There is the notion of Generalized RBF Kernels, for example in "Towards Optimal Bag-of-Features for Object Categorization and Semantic Video Retrieval" from Jiang (1) or in formula (2.72) in ...
1answer
117 views

3answers
624 views

### Support vector machine for text classification

I am currently having a data set, class 1 with about 8000 short text files and class 2 with about 3000 short text files. I applied LibSVM and tried a couple of parameter combinations in the ...
2answers
170 views

### Does a linear SVM behave in the same way as correlation except with the imposition of a large margin?

I want to understand the relationship between correlation and SVMs. My question is based on initial studies that used correlation as a way to examine distributed processing in the cortex with fMRI. ...
2answers
1k views

### How to select best parameter for polynomial kernel?

I am using LibSVM library for classification. For my problem I am using polynomial kernel and I need to select best parameters (d = degree of polynomial kernel, and ...
4answers
258 views

### Kernel Selection

I am not an expert in SVM and kernel, so please excuse me if I ask stupid question. Actually, first I want to know how to analyze a dataset to discover its pattern. And second, how can I select ...
0answers
270 views

### SVM using RBF and nearest neighbor classification method

SVM using RBF kernel is claimed to be similar (equivalent) to the K nearest neighbor classification method. I am not very clear about the analysis process of building this kind of relationship. Thanks ...
2answers
875 views

### Kernel logistic regression

I heard Kernel Logistic Regression is a classical combination of kernel methods and Logistic regression, but I cannot find any major reference (book, or paper) on this topic. Can you give me any ...
2answers
325 views

### Polynomial kernel function

Consider SMV with the polynomial kernel $k(x_1,x_2)=(\langle x_1, x_2\rangle + 1)^d,$ where $d > 1.$ Is it true that if the dataset is separated with a hyperplane then the SVM (with the kernel $k$) ...
1answer
325 views

### Parameters to change for different kernels for SVM

I am carrying out SVM and was interested in knowing the parameters that could be varied for each kernel. I am using 3 kernels: RBF, linear and polynominal. These are the parameters that i think can ...
1answer
300 views

### What is a kernel and what sets it apart from other functions

There seem to be many machine learning algorithms that rely on kernel functions. SVMs and NNs to name but two. So what is the definition of a kernel function and what are the requirements for it to be ...
3answers
1k views

### Train a SVM-based classifier while taking into account the weight information

Currently I have a data set which are known to belong to two classes, and would like to build a classifier using SVM. However, there exist different confidence levels for this data set. For example, ...
1answer
207 views