e/Winnow algorithm

Information
has gloss	eng: The winnow algorithm is a technique from machine learning for learning a linear classifier from labeled examples. It is very similar to the perceptron algorithm. However, the perceptron algorithm uses an additive weight-update scheme, but winnow uses a multiplicative weight-update scheme that allows it to perform much better when many dimensions are irrelevant (hence its name). It is not a sophisticated algorithm but it scales well to high-dimensional spaces. During training, winnow is shown a sequence of positive and negative examples. From these it learns a decision hyperplane. It can also be used in the online learning setting, where the learning phase is not separated from the training phase.
lexicalization	eng: Winnow algorithm
lexicalization	eng: Winnow
instance of	c/Classification algorithms