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» Unsupervised Feature Selection Using Feature Similarity
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IJON
2000
71views more  IJON 2000»
15 years 2 months ago
Variable selection using neural-network models
In this paper we propose an approach to variable selection that uses a neural-network model as the tool to determine which variables are to be discarded. The method performs a bac...
Giovanna Castellano, Anna Maria Fanelli
VLDB
1999
ACM
118views Database» more  VLDB 1999»
15 years 6 months ago
Similarity Search in High Dimensions via Hashing
The nearest- or near-neighbor query problems arise in a large variety of database applications, usually in the context of similarity searching. Of late, there has been increasing ...
Aristides Gionis, Piotr Indyk, Rajeev Motwani
SAT
2009
Springer
111views Hardware» more  SAT 2009»
15 years 9 months ago
Restart Strategy Selection Using Machine Learning Techniques
Abstract. Restart strategies are an important factor in the performance of conflict-driven Davis Putnam style SAT solvers. Selecting a good restart strategy for a problem instance...
Shai Haim, Toby Walsh
WSCG
2003
191views more  WSCG 2003»
15 years 3 months ago
Binary Histogram in Image Classification for Retrieval Purposes
Image retrieval can be considered as a classification problem. Classification is usually based on some image features. In the feature extraction image segmentation is commonly use...
Iivari Kunttu, Leena Lepistö, Juhani Rauhamaa...
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APIN
2004
131views more  APIN 2004»
15 years 2 months ago
Rough Self Organizing Map
A rough self-organizing map (RSOM) with fuzzy discretization of feature space is described here. Discernibility reducts obtained using rough set theory are used to extract domain k...
Sankar K. Pal, Biswarup Dasgupta, Pabitra Mitra