Winnow (algorithm): Difference between revisions

Revision as of 21:16, 14 September 2008

Revision as of 21:19, 14 September 2008

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The basic algorithm, Winnow1, is given as follows.

The instance space is <math>X=\{0,1\}^n</math>. The algorithm maintains non-negative weights <math>w_i</math> for <math>i\in \{1...n\}</math> which are initially set to 1. When the learner is given an example $<math>(x_1,...x_n)$</math>, the learner follows the following prediction rule:

* '''If''' <math>\sum_{i=1}^n w_i x_i > \Theta </math>, '''then''' it predicts 1