On the characterization of noise filters for self-training semi-supervised in nearest neighbor classification

Neurocomputing

Volumn 132, Issue , 2014, Pages 30-41

  Triguero, Isaac ^a   Sáez, José A ^a   Luengo, Julián ^b   García, Salvador ^c   Herrera, Francisco ^a  

^a UNIVERSITY OF GRANADA   (Spain)

^b UNIVERSITY OF BURGOS   (Spain)

^c UNIVERSITY OF JAÉN   (Spain)

Author keywords

Nearest neighbor classification; Noise filters; Noisy data; Self training; Semi supervised learning

Indexed keywords

NEAREST NEIGHBOR CLASSIFICATION; NOISE FILTERS; NOISY DATA; SELF-TRAINING; SEMI-SUPERVISED LEARNING;

FORECASTING; SUPERVISED LEARNING;

CLASSIFICATION (OF INFORMATION);

ALL KNN; ANALYTICAL ERROR; ARTICLE; CLASSIFICATION ALGORITHM; CLASSIFICATION FILTER; COMPARATIVE STUDY; CUT EDGES WEIGHT STATISTIC; DATA ANALYSIS; DATA PROCESSING; EDITED NEAREST NEIGHBOR; EDITED NEAREST NEIGHBOR ESTIMATING CLASS PROBABILISTIC AND THRESHOLD; EMPIRICAL RESEARCH; HUMAN; ITERATIVE PARTITIONING FILTER; K NEAREST NEIGHBOR; MODIFIED EDITED NEAREST NEIGHBOR; MULTIEDIT; NEAREST CENTROID NEIGHBOR EDITION; NOISE FILTER; NONPARAMETRIC TEST; PREDICTION; PRIORITY JOURNAL; PROBLEM SOLVING; RELATIVE NEIGHBORHOOD GRAPH EDITION; SEMI SUPERVISED CLASSIFICATION; SYSTEM ANALYSIS;

EID: 84896737995     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2013.05.055     Document Type: Article

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