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On the Use of Variable Complementarity for Feature Selection in Cancer Classification

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What this work says

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

inferredcites →https://doi.org/10.1002/0471200611openalex-snapshot

Elements of Information Theory

inferredcites →https://doi.org/10.1002/9780470316849openalex-snapshot

Multivariate Density Estimation

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Artificial Neural Networks and Neural Information Processing — ICANN/ICONIP 2003

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A Comparative Evaluation of Sequential Feature Selection Algorithms

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Learning Bayesian Networks Using Feature Selection

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Elements of Information Theory

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Greedy Attribute Selection

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Relevance measures for subset variable selection in regression problems based on -additive mutual information

inferredcites →https://doi.org/10.1016/s0004-3702(97)00043-xopenalex-snapshot

Wrappers for feature subset selection

inferredcites →https://doi.org/10.1016/s0004-3702(97)00063-5openalex-snapshot

Selection of relevant features and examples in machine learning

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A Formalism for Relevance and Its Application in Feature Subset Selection

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Lecture Notes in Computer Science 1205

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10.1162/153244303322753616

What points at this work

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

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Information‐Theoretic Gene Selection In Expression Data

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