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An Empirical Comparison of Three Boosting Algorithms on Real Data Sets with Artificial Class Noise

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Boosting a Weak Learning Algorithm by Majority

inferredcites →https://doi.org/10.1006/jcss.1997.1504openalex-snapshot

A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting

inferredcites →https://doi.org/10.1007/3-540-45014-9_8openalex-snapshot

Some Results on Weakly Accurate Base Learners for Boosting Regression and Classification

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A desicion-theoretic generalization of on-line learning and an application to boosting

inferredcites →https://doi.org/10.1023/a:1007515423169openalex-snapshot

An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants

inferredcites →https://doi.org/10.1023/a:1007607513941openalex-snapshot

An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees: Bagging, Boosting, and Randomization

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Improved Boosting Algorithms Using Confidence-rated Predictions

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An Adaptive Version of the Boost by Majority Algorithm

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The Strength of Weak Learnability

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Improved boosting algorithms using confidence-rated predictions

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A Theory of the Learnable

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10.1162/15324430152733133

inferredcites →https://doi.org/10.1214/aos/1016218223openalex-snapshot

Additive logistic regression: a statistical view of boosting (With discussion and a rejoinder by the authors)

inferredcites →https://doi.org/10.1214/aos/1024691352openalex-snapshot

Boosting the margin: a new explanation for the effectiveness of voting methods

inferredcites →https://doi.org/10.2307/1270579openalex-snapshot

Construction and Assessment of Classification Rules

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Classification and Regression Trees.

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Classification and Regression Trees.

inferredcites →https://doi.org/10.2307/2533581openalex-snapshot

Construction and Assessment of Classification Rules.

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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