Empirical measure of multiclass generalization performance: The K-winner machine case

IEEE Transactions on Neural Networks

Volumn 12, Issue 6, 2001, Pages 1525-1529

  Ridella, S ^a   Zunino, R ^a  

^a UNIVERSITY OF GENOA   (Italy)

Author keywords

Generalization theory; K winner machine; VC dimension; Vector quantization

Indexed keywords

COMPUTER SIMULATION; DATA STRUCTURES; DATABASE SYSTEMS; MONTE CARLO METHODS; OPTICAL CHARACTER RECOGNITION; SET THEORY; VECTOR QUANTIZATION;

GENERALIZATION THEORY; K-WINNER MACHINE; VAPNIK-CHERVONENKIS DIMENSION;

LEARNING SYSTEMS;

EID: 0035505574     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/72.963791     Document Type: Letter

References (8)

1. Measuring the VC-dimension of a learning machine
2. Measuring the VC-dimension using optimized experimental design
3. K-winner machines for pattern classification
4. A support vector method for clustering