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Monotonicity Maintenance in Information-Theoretic Machine Learning Algorithms

https://doi.org/10.1007/bf00994659
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Outgoing claims: the papers this work cites, builds on, or argues with.

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Machine Learning
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LEARNING EFFICIENT CLASSIFICATION PROCEDURES AND THEIR APPLICATION TO CHESS END GAMES
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The use of background knowledge in decision tree induction
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The CN2 Induction Algorithm
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A distance-based attribute selection measure for decision tree induction
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Systematic research into human behavior in multiattribute object classification problems
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A theory and methodology of inductive learning
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The Use of Background Knowledge in Decision Tree Induction
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A Distance-Based Attribute Selection Measure for Decision Tree Induction
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Incremental Induction of Decision Trees
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Brand Choice Behavior as a Function of Information Load: Replication and Extension
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Assessing Credit Card Applications Using Machine Learning
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Learning and classification of monotonic ordinal concepts
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Automatic Generation of Symbolic Multiattribute Ordinal Knowledge‐Based DSSs: Methodology and Applications*
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Building Expert Systems

What points at this work

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

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Monotonicity Detection and Enforcement in Longitudinal Classification
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Managing Monotonicity in Classification by a Pruned AdaBoost
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Monotonicity in Ant Colony Classification Algorithms
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A First Attempt on Monotonic Training Set Selection
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Consistent Representation of Rankings
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Monotone Instance Ranking with mira
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Induction of Ordinal Classification Rules from Incomplete Data
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Fonctions latticielles polynomiales pour l’interpolation et la classification monotone
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