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» Learning fault-tolerance in Radial Basis Function Networks
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KDD
1998
ACM
112views Data Mining» more  KDD 1998»
13 years 11 months ago
Evaluating Usefulness for Dynamic Classification
This paper develops the concept of usefulness in the context of supervised learning. We argue that usefulness can be used to improve the performance of classification rules (as me...
Gholamreza Nakhaeizadeh, Charles Taylor, Carsten L...
ENVSOFT
2008
115views more  ENVSOFT 2008»
13 years 7 months ago
Adaptive fuzzy modeling versus artificial neural networks
In this paper two areas of soft computing (fuzzy modeling and artificial neural networks) are discussed. Based on the fundamental mathematical similarity of fuzzy technique and ra...
Ralf Wieland, Wilfried Mirschel
NPL
2006
172views more  NPL 2006»
13 years 7 months ago
Adapting RBF Neural Networks to Multi-Instance Learning
In multi-instance learning, the training examples are bags composed of instances without labels, and the task is to predict the labels of unseen bags through analyzing the training...
Min-Ling Zhang, Zhi-Hua Zhou
ICAISC
2004
Springer
14 years 22 days ago
Optimization of Centers' Positions for RBF Nets with Generalized Kernels
The problem of locating centers for radial basis functions in neural networks is discussed. The proposed approach allows us to apply the results from the theory of optimum experime...
Ewaryst Rafajlowicz, Miroslaw Pawlak
FUZZY
1994
Springer
194views Fuzzy Logic» more  FUZZY 1994»
13 years 11 months ago
Improving a Fuzzy Inference System by Means of Evolution Strategy
In this paper, evolution strategy is applied in order to improve the time series prediction accuracy of a Sugeno and Takagi type fuzzy inference system FIS. The presented approach...
Willfried Wienholt