Questions tagged [max-margin]

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Interpretation/Intuition for L2 Regularization in Neural Networks [duplicate]

When we use L1-regularization in neural networks, it is pretty intuitive how the regularization will influence the learned weights. Namely, weights will not become needlessly large and unimportant ...
1 vote
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Show that solution for the maximum margin hyperplane is unchanged when w.x + b = (+/-) 1 is replaced by arbitrary constant $\gamma$?

How to show that solution for the maximum margin hyperplane for hard-margin SVM is unchanged when w.x + b = (+/-) 1 is replaced by arbitrary constant $\gamma$? In the derivation for the SVM, we ...
3 votes
1 answer

Relationship between L1 penalty and margin in SVM

Expanding on "Why aren't there there two regularization terms in SVC?" and "Meaning of penalty and loss in ...
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Does gradient descent for linear regression selects the minimal norm solution?

I was told that Gradient Descent finds the weights of smallest norm. This is what I understood in the linear regression setting: $f_w(x)=w^\top x$ are the linear functions $ \mathbb{R}^n \rightarrow \...
0 votes
1 answer

How to calculate the margin in SVM light?

I'm using Support Vector Machine in a project. The library chosen is SVM light of Joachims: I have the need to calculate the margin. Namely, given a training set of ...
1 vote
1 answer

IS optimization unnecessary in SVM?

According to here, Now knowing the $a_i$ we can find the weights $w$ for the maximal margin separating hyperplane: \begin{align*} w = \sum_{i=1}^{l} a_i y_i x_i \end{align*} I cannot understand what ...
22 votes
1 answer

Interpreting distance from hyperplane in SVM

I have a few doubts in understanding SVMs intuitively. Assume we have trained a SVM model for classification using some standard tool like SVMLight or LibSVM. When we use this model for prediction ...
11 votes
1 answer

What's the relationship between an SVM and hinge loss?

My colleague and I are trying to wrap our heads around the difference between logistic regression and an SVM. Clearly they are optimizing different objective functions. Is an SVM as simple as saying ...
1 vote
1 answer

CRF Training: Max-margin vs max-likelihood

I'm trying to use PyStruct's CRF implementation. In its user guide, it says the following: I call these models Conditional Random Fields (CRFs), but this a slight abuse of notation, as PyStruct ...
6 votes
2 answers

Is there a way to remove individual trees from a forest in the randomForest package in R?

I am trying to implement the ideas in this paper: This requires me to be able to remove individual trees from the forest and ...
2 votes
0 answers

Linear SVM decision boundary after a linear transformation of data

Let $w$ be the decision boundary of a linear SVM trained on the dataset $D=\{(x_i, y_i)_{i=1}^N\}$. Suppose we apply a linear transformation A to examples $x_i$s and obtain a new dataset $D'=\{(z_i, ...
3 votes
1 answer

Max-margin clustering with size constraint

Given a dataset $D$ and a distance measure, I want to split the dataset into two disjoint subsets $X, Y$ of a specified size (say 80% and 20% of the original size), so that the minimum distance of all ...