Linked Questions
42 questions linked to/from How does a Support Vector Machine (SVM) work?
1
vote
1
answer
763
views
SVM: intuition behind maximizing the margin [duplicate]
I do understand that SVM is about finding the classifier that maximize the margin. But what is the intuition there? Please don't go into the math. Thx
More specifically, if someone ask you during an ...
- 11
0
votes
0
answers
528
views
Mathematical formulation SVM Model [duplicate]
Good morning,
For a homework I used a support vector machines (classification) with a RBF kernel, k-fold cross validation=10, cost of constraints violation=100, and gamma=0.001.
It works great and ...
- 415
1
vote
2
answers
281
views
SVM mathematical background [duplicate]
I try to get the basic understanding behing SVM algorithm, however I have a problem with basic mathematics.
I follow the lecture Support Vector Machine.
Suppose the two classes can be separated by ...
- 777
0
votes
0
answers
206
views
What is the intuition behind slack variables, penalty and minimization of support vector machines? [duplicate]
I would like to understand more deeply what the purpose and intuition of slack variables is in support vector machines.
I know that slack variables are used to minimize
$\frac{1}{2} ||w||^2 + C \sum_{...
- 135
1
vote
0
answers
111
views
what is weight vector and bias in svm [duplicate]
I'm trying to understand the SVM algorithm but not able to understand what weight vector and bias is ? Could anyone explain it in laymen terms.
- 111
0
votes
0
answers
29
views
What is the math behind predict() in e1071 for SVM? [duplicate]
I have no math or computer science training.
When I run predict(svm,data,type="class")
R spits out a prediction of 1 or 0 for each row of data. What is it doing ...
- 57
179
votes
8
answers
343k
views
What is the influence of C in SVMs with linear kernel?
I am currently using an SVM with a linear kernel to classify my data. There is
no error on the training set. I tried several values for the parameter $C$
($10^{-5}, \dots, 10^2$). This did not ...
- 2,535
107
votes
4
answers
91k
views
How to select kernel for SVM?
When using SVM, we need to select a kernel.
I wonder how to select a kernel. Any criteria on kernel selection?
- 6,949
62
votes
5
answers
120k
views
How does one interpret SVM feature weights?
I am trying to interpret the variable weights given by fitting a linear SVM.
(I'm using scikit-learn):
...
69
votes
5
answers
48k
views
Why bother with the dual problem when fitting SVM?
Given the data points $x_1, \ldots, x_n \in \mathbb{R}^d$ and labels $y_1, \ldots, y_n \in \left \{-1, 1 \right\}$, the hard margin SVM primal problem is
$$ \text{minimize}_{w, w_0} \quad \frac{1}{2} ...
- 2,488
61
votes
4
answers
93k
views
Comparing SVM and logistic regression
Can someone please give me some intuition as to when to choose either SVM or LR? I want to understand the intuition behind what is the difference between the optimization criteria of learning the ...
- 661
82
votes
1
answer
8k
views
Help me understand Support Vector Machines
I understand the basics of what a Support Vector Machines' aim is in terms of classifying an input set into several different classes, but what I don't understand is some of the nitty-gritty details. ...
- 1,187
42
votes
4
answers
14k
views
How can SVM 'find' an infinite feature space where linear separation is always possible?
What is the intuition behind the fact that an SVM with a Gaussian Kernel has infinite dimensional feature space?
- 561
39
votes
2
answers
57k
views
Which search range for determining SVM optimal C and gamma parameters?
I am using SVM for classification and I am trying to determine the optimal parameters for linear and RBF kernels. For the linear kernel I use cross-validated parameter selection to determine C and for ...
- 391
25
votes
1
answer
31k
views
What function could be a kernel?
In the context of machine learning and pattern recognition, there's a concept called Kernel Trick. Facing problems where I am asked to determine whether a function could be a kernel function or not, ...
- 785