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Winnow (algorithm)

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, while Winnow uses a multiplicative scheme that allows it to perform much better when many dimensions are irrelevant…

Algorithm, Mistake bounds & Overview

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Explore the main themes, entities and connections around Winnow (algorithm). Start with the topic map, then use the sections below for research and deeper semantic analysis.

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Topics to explore

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Overview

Algorithm

Mistake bounds

Advanced semantic analysis

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Map overview Semantic statistics

Winnow (algorithm)

Nodes15
Edges14
Triples0
Avg. degree1.87
Density0.133333
Components1

How this topic connects Entity context

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Important terminology Word statistics

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Important terminology

algorithm winnow displaystyle examples set weights example learning perceptron positive negative used hyperplane ldots weight feature theta number step linear

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc

Related concept clusters Concept neighborhoods

These clusters group vocabulary that occurs around closely connected concepts in the source material.

    Connections between topic areas Semantic bridges

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    Min side: 3
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