##### Department of Mathematics,

University of California San Diego

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### Center for Computational Mathematics Seminar

## Olvi Mangasarian

#### UCSD

## The Disputed Federalist Papers: Resolution via Support Vector Machine Feature Selection

##### Abstract:

In this talk we utilize a support vector machine feature selection procedure via concave minimization to solve the well-known Disputed Federalist Papers classification problem. First we find a separating plane that classifies correctly all the training set consisting of papers of known authorship, based on the relative frequencies of three words only. Then, using this three-dimensional separating plane, all of the 12 disputed papers ended up on one side of the separating plane. Our result coincides with previous statistical and combinatorial method results.

### January 21, 2014

### 10:00 AM

### AP&M 2402

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