# Tag Info

### How do I deal with unbalance classes in a stock market prediction problem?

There is a perfect mapping between the rule and the decision. You know the percentage change; now apply your rule to map that to a buy/sell/hold decision. There is no machine learning to do, but even ...
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1 vote
Accepted

### What are some methods to reduce a dataframe so I can pass it as one sample to an SVM?

SVM are not meant to solve "arbitrarily long" classification problem, therefore you have few choices: use PCA for sequences, however it takes very long since it has to build a giant matrix ...

### What are some methods to reduce a dataframe so I can pass it as one sample to an SVM?

The standard is to take the mean across each sentence, leaving you with a vector for each participant. From there you can use t-SNE, UMAP or PCA to reduce the size of each vector.

### Why do we take +1. -1 for support vector hyperplane in SVM?

This is an excellent question and one I struggled with as well. Firstly, the margin is not fixed. As your diagram shows, the margin $m = \frac{2}{\lVert w \rVert}$, which is a function of the 2-norm ...

### SVDD vs once Class SVM

The one-class support vector machines (OCSVM) is a one-class classification technique similar to the SVDD. Instead of obtaining a bounding hypersphere around the training data, the OCSVM algorithm ...
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### Why would we add regularization loss to the gradient itself in an SVM?

The l2 regularization term is being added to the loss itself. But then you need to find the gradient of this new loss; since gradients are additive, this is the same as the gradient of the unpenalized ...
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