The one-inclusion graph algorithm is near-optimal for the prediction model of learning

IEEE Transactions on Information Theory

Volumn 47, Issue 3, 2001, Pages 1257-1261

  Li, Y ^a   Long, P M ^a   Srinivasan, A ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

Computational learning; One inclusion graph algorithm; Prediction model; Sample complexity; Vapnik Chervonenkis (VC) dimension

Indexed keywords

COMPUTATIONAL COMPLEXITY; COMPUTATIONAL METHODS; COMPUTER SIMULATION; ERRORS; GRAPH THEORY; PROBABILITY; RANDOM PROCESSES;

COMPUTATIONAL LEARNING; ONE INCLUSION GRAPH ALGORITHM; PREDICTION MODEL; VAPNIK-CHERVONENKIS DIMENSION;

ALGORITHMS;

EID: 0035269626     PISSN: 00189448     EISSN: None     Source Type: Journal    
DOI: 10.1109/18.915700     Document Type: Letter

References (8)