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Probabilistic-Weighted k-Nearest-Neighbour Algorithm: a New Approach for Gene Expression Based Classification  (Make Corrections)  
Basilio Sierra, Elena Lazkano



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Abstract: The k-Nearest-Neighbour (KNN) decision rule has often been used in Pattern Recognition problems. One of the diculties that arises when utilizing this technique is that each of the labeled samples is given equal importance in deciding the class memberships of the pattern to be classi ed, regardless of the "typicalness" of each of the neighbours. (Update)

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@misc{ sierra-probabilisticweighted,
  author = "Basilio Sierra and Elena Lazkano",
  title = "Probabilistic-Weighted k-Nearest-Neighbour Algorithm: a New Approach for
    Gene Expression Based Classification",
  url = "citeseer.ist.psu.edu/764468.html" }
Citations (may not include all citations):
760   Probabilistic Reasoning in Intelligent Systems (context) - Pearl - 1988
233   The CN2 induction algorithm - Clark, Nibblet - 1989
164   A study of cross-validation and bootstrap for accuracy estim.. - Kohavi - 1995
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14   Predicting survival in malignant skin melanoma using bayesia.. - Sierra, naga - 1998
13   Feature Selection for High-Dimensional Genomic Microarray Da.. - Xing, Jordan et al.
11   Tissue Classi- cation with Gene Expression Pro les (context) - Ben-Dor, Bruhn et al. - 2000
6   Machine learning inspired approaches to combine standard med.. (context) - Sierra, Serrano et al. - 1999
5   Computational Analysi Leukemia Microarray Expression Data Us.. (context) - Darden, Analysis et al.
5   How many genes are needed for a discriminant microarray data.. (context) - Li, Yang
4   A Ranking Method to Improve Detection of Disease Using Selec.. (context) - Aris, Recce
4   Selection of Informative Genes in Gene Expression Based Diag.. (context) - Beibel

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