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Approximate statistical tests for comparing supervised classification learning algorithms

Author:

Thomas G. DietterichAuthors Info & Claims

Neural Computation, Volume 10, Issue 7

Pages 1895 - 1923

https://doi.org/10.1162/089976698300017197

Published: 01 October 1998 Publication History

Abstract

No abstract available.

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Index Terms

Approximate statistical tests for comparing supervised classification learning algorithms
1. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Supervised learning
        Supervised learning by classification
    2. Machine learning approaches
      1. Classification and regression trees
      2. Neural networks
2. Mathematics of computing
  1. Mathematical software
  2. Probability and statistics

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Published In

Neural Computation Volume 10, Issue 7

Oct. 1998

329 pages

ISSN:0899-7667

Editor:
Terrence Sejnowski
Univ. of California at San Diego

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MIT Press

Cambridge, MA, United States

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Published: 01 October 1998

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Ensembles for Supervised Classification Learning

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Comparing ensemble learning approaches in genetic programming for classification with unbalanced data

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