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» Classifying Relational Data with Neural Networks
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FLAIRS
2008
15 years 3 months ago
Evolutionary Learning of Dynamic Naive Bayesian Classifiers
Naive Bayesian classifiers work well in data sets with independent attributes. However, they perform poorly when the attributes are dependent or when there are one or more irrelev...
Miguel A. Palacios-Alonso, Carlos A. Brizuela, Lui...
IJCAI
1997
15 years 2 months ago
On the Role of Hierarchy for Neural Network Interpretation
In this paper, we concentrate on the expressive power of hierarchical structures in neural networks. Recently, the so-called SplitNet model was introduced. It develops a dynamic n...
Jürgen Rahmel, Christian Blum, Peter Hahn
ICANN
2007
Springer
15 years 7 months ago
Boosting Unsupervised Competitive Learning Ensembles
Topology preserving mappings are great tools for data visualization and inspection in large datasets. This research presents a combination of several topology preserving mapping mo...
Emilio Corchado, Bruno Baruque, Hujun Yin
BMCBI
2004
133views more  BMCBI 2004»
15 years 1 months ago
Artificial neural network approach for selection of susceptible single nucleotide polymorphisms and construction of prediction m
Background: Screening of various gene markers such as single nucleotide polymorphism (SNP) and correlation between these markers and development of multifactorial disease have pre...
Yasuyuki Tomita, Shuta Tomida, Yuko Hasegawa, Yoic...
ISMB
1994
15 years 2 months ago
DNA Sequence Analysis Using Hierarchical ART-based Classification Network
Adaptive resonance theory (ART)describes a class of artificial neural networkarchitectures that act as classification tools whichself-organize, workin realtime, and require no ret...
Cathie LeBlanc, Charles R. Katholi, Thomas R. Unna...