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Optimal constraint-based decision tree induction from itemset lattices
by
Fromont, Elisa
, Nijssen, Siegfried
in
Algorithms
/ Artificial Intelligence
/ Chemistry and Earth Sciences
/ Computer Science
/ Data Mining and Knowledge Discovery
/ Decision trees
/ Heuristic
/ Information Storage and Retrieval
/ Joints
/ Lattices
/ Learning
/ Machine Learning
/ Mining
/ Optimization
/ Performance evaluation
/ Physics
/ Post-processing
/ State of the art
/ Statistics for Engineering
2010
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Optimal constraint-based decision tree induction from itemset lattices
by
Fromont, Elisa
, Nijssen, Siegfried
in
Algorithms
/ Artificial Intelligence
/ Chemistry and Earth Sciences
/ Computer Science
/ Data Mining and Knowledge Discovery
/ Decision trees
/ Heuristic
/ Information Storage and Retrieval
/ Joints
/ Lattices
/ Learning
/ Machine Learning
/ Mining
/ Optimization
/ Performance evaluation
/ Physics
/ Post-processing
/ State of the art
/ Statistics for Engineering
2010
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Do you wish to request the book?
Optimal constraint-based decision tree induction from itemset lattices
by
Fromont, Elisa
, Nijssen, Siegfried
in
Algorithms
/ Artificial Intelligence
/ Chemistry and Earth Sciences
/ Computer Science
/ Data Mining and Knowledge Discovery
/ Decision trees
/ Heuristic
/ Information Storage and Retrieval
/ Joints
/ Lattices
/ Learning
/ Machine Learning
/ Mining
/ Optimization
/ Performance evaluation
/ Physics
/ Post-processing
/ State of the art
/ Statistics for Engineering
2010
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Optimal constraint-based decision tree induction from itemset lattices
Journal Article
Optimal constraint-based decision tree induction from itemset lattices
2010
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Overview
In this article we show that there is a strong connection between decision tree learning and local pattern mining. This connection allows us to solve the computationally hard problem of finding
optimal
decision trees in a wide range of applications by post-processing a set of patterns: we use local patterns to construct a global model. We exploit the connection between constraints in pattern mining and constraints in decision tree induction to develop a framework for categorizing decision tree mining constraints. This framework allows us to determine which model constraints can be pushed deeply into the pattern mining process, and allows us to improve the state-of-the-art of optimal decision tree induction.
Publisher
Springer US,Springer Nature B.V,Springer
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