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Iterative rule induction methods

https://doi.org/10.1007/bf00117745
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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/j.1538-7305.1956.tb03835.xopenalex-snapshot
Minimization of Boolean Functions*
inferredcites →https://doi.org/10.1007/bf00058679openalex-snapshot
Classifier Systems and the Animat Problem
inferredcites →https://doi.org/10.1007/bf00116251openalex-snapshot
Induction of Decision Trees
inferredcites →https://doi.org/10.1007/bf00116835openalex-snapshot
The CN2 Induction Algorithm
inferredcites →https://doi.org/10.1007/bf00355545openalex-snapshot
Connectionistic models of boolean category representation
inferredcites →https://doi.org/10.1016/0004-3702(90)90037-zopenalex-snapshot
Maximizing the predictive value of production rules
inferredcites →https://doi.org/10.1016/b978-0-934613-64-4.50019-0openalex-snapshot
An Empirical Comparison of Genetic and Decision-Tree Classifiers
inferredcites →https://doi.org/10.1016/b978-1-55860-036-2.50038-2openalex-snapshot
TWO ALGORITHMS THAT LEARN DNF BY DISCOVERING RELEVANT FEATURES
inferredcites →https://doi.org/10.1016/s0020-7373(87)80053-6openalex-snapshot
Simplifying decision trees
inferredcites →https://doi.org/10.1109/ijcnn.1989.118273openalex-snapshot
Neural network learning time: effects of network and training set size
inferredcites →https://doi.org/10.1109/ijcnn.1989.118726openalex-snapshot
Efficient training of the backpropagation network by solving a system of stiff ordinary differential equations
inferredcites →https://doi.org/10.1111/j.2517-6161.1987.tb01695.xopenalex-snapshot
Estimation and Inference by Compact Coding
inferredcites →https://doi.org/10.1162/neco.1989.1.4.470openalex-snapshot
Sigmoids Distinguish More Efficiently Than Heavisides
inferredcites →https://doi.org/10.1287/opre.21.2.498openalex-snapshot
An Effective Heuristic Algorithm for the Traveling-Salesman Problem
inferredcites →https://doi.org/10.2307/2288003openalex-snapshot
Classification and Regression Trees.

What points at this work

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

inferred← citeshttps://doi.org/10.1007/3-540-60025-6_157openalex-snapshot
Induction of expert system rules from databases based on rough set theory and resampling methods
inferred← citeshttps://doi.org/10.1007/3-540-61286-6_138openalex-snapshot
Induction of expert system rules from databases based on rough set theory and Resampling methods
inferred← citeshttps://doi.org/10.1007/978-3-642-58648-4_11openalex-snapshot
New Directions in Text Categorization
inferred← citeshttps://doi.org/10.1017/s0890060400000469openalex-snapshot
Use of decision-tree induction for process optimization and knowledge refinement of an industrial process
inferred← citeshttps://doi.org/10.1023/a:1007626017208openalex-snapshot
Constructing X-of-N Attributes for Decision Tree Learning
inferred← citeshttps://doi.org/10.1080/00207160.2011.613460openalex-snapshot
Interpretability of fuzzy association rules as means of discovering threats to privacy
inferred← citeshttps://doi.org/10.1109/64.248354openalex-snapshot
Optimized rule induction
inferred← citeshttps://doi.org/10.1109/cec.2016.7744274openalex-snapshot
Enhancing discrimination power with genetic feature construction: A grammatical evolution approach
inferred← citeshttps://doi.org/10.1109/icassp.1994.389224openalex-snapshot
Automatic generation of prosodic rules for speech synthesis
inferred← citeshttps://doi.org/10.1111/j.1467-8640.1995.tb00040.xopenalex-snapshot
PRIMEROSE: PROBABILISTIC RULE INDUCTION METHOD BASED ON ROUGH SETS AND RESAMPLING METHODS
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