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FUZZIEEE
2007
IEEE
14 years 3 months ago
Genetic Learning of Membership Functions for Mining Fuzzy Association Rules
— Data mining is most commonly used in attempts to induce association rules from transaction data. Most previous studies focused on binary-valued transaction data. Transaction da...
Rafael Alcalá, Jesús Alcalá-F...
PKDD
2009
Springer
181views Data Mining» more  PKDD 2009»
14 years 3 months ago
Active Learning for Reward Estimation in Inverse Reinforcement Learning
Abstract. Inverse reinforcement learning addresses the general problem of recovering a reward function from samples of a policy provided by an expert/demonstrator. In this paper, w...
Manuel Lopes, Francisco S. Melo, Luis Montesano
ESANN
2003
13 years 10 months ago
Robust Topology Representing Networks
Martinetz and Schulten proposed the use of a Competitive Hebbian Learning (CHL) rule to build Topology Representing Networks. From a set of units and a data distribution, a link i...
Michaël Aupetit
KDD
1998
ACM
99views Data Mining» more  KDD 1998»
14 years 28 days ago
Learning to Predict the Duration of an Automobile Trip
In this paper, weexplore the use of machinelearning and data mining to improvethe prediction of travel times in an automobile. Weconsider two formulations of this problem, one tha...
Simon Handley, Pat Langley, Folke A. Rauscher
KDD
2006
ACM
113views Data Mining» more  KDD 2006»
14 years 9 months ago
A new efficient probabilistic model for mining labeled ordered trees
Mining frequent patterns is a general and important issue in data mining. Complex and unstructured (or semi-structured) datasets have appeared in major data mining applications, i...
Kosuke Hashimoto, Kiyoko F. Aoki-Kinoshita, Nobuhi...