When are k-nearest neighbor and back propagation accurate for feasible sized sets of examples?

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 412 LNCS, Issue , 1990, Pages 2-25

  Baum, Eric B ^a  

^a NEC LABORATORIES AMERICA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BACKPROPAGATION; CLASSIFICATION (OF INFORMATION); GEOMETRY; MOTION COMPENSATION; NEAREST NEIGHBOR SEARCH; PATTERN RECOGNITION;

EXPERIMENTAL TEST; K NEAREST NEIGHBOR ALGORITHM; K-NEAREST NEIGHBORS; LOWER AND UPPER BOUNDS; RANDOM TARGETS; TARGET FUNCTIONS; UNIFORM DISTRIBUTION; VAPNIK-CHERVONENKIS DIMENSIONS;

FEEDFORWARD NEURAL NETWORKS;

EID: 84957345624     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-52255-7_24     Document Type: Conference Paper

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