Nearest neighbor ensemble

Proceedings - International Conference on Pattern Recognition

Volumn 1, Issue , 2004, Pages 228-231

  Domeniconi, Carlotta ^a   Yan, Bojun ^a  

^a George Mason University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ENSEMBLES; GENERALIZATION ERRORS; HIGH DIMENSIONALITY; TRAINING SETS;

CORRELATION METHODS; DATA REDUCTION; ERROR ANALYSIS; PROBABILITY; SAMPLING; TREES (MATHEMATICS);

PATTERN RECOGNITION;

EID: 10044234903     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPR.2004.1334065     Document Type: Conference Paper

References (17)

1. A. Agresti. Categorical data analysis. John Wiley & Sons, New York, 1990.
2. K. M. Ali and M. J. Pazzani. Error reduction through learning multiple descriptions. Machine Learning, 24:173-202, 1996.
3. S. D. Bay. Nearest neighbor classification from multiple feature subsets. Intelligent Data Analysis, 3(3): 191 -209, 1999.
4. C. L. Blake and C. J. Merz, UCI repository of machine learning databases University of California, Department of Information and Computer Science, 1998.
5. L. Breiman. Bagging predictors. Machine Learning 24:123-140, 1996.
6. L. Breiman. Prediction games and arcing algorithms. Neural Computation 11:1493-1517, 1999.
7. J. de Borda. Memoire sur les elections au scrutin, historie de l'academie royale des sciences. Paris, 1781.
8. C. Domeniconi and D. Gunopulos. Adaptive nearest neighbor classification using support vector machines. Advances in Neural Information Processing Systems 14, MIT Press, 2002.
9. C. Domeniconi, J. Peng, and D. Gunopulos. Locally adaptive metric nearest neighbor classification. IEEE Trans on Pattern Analysis and Machine Intelligence, 24(9): 1281-1285, 2002.
10. P. Chan and S. Stolfo. A comparative evaluation of voting and meta-learning on partitioned data. Twelfth International Conference on Machine Learning, 1995.
11. Y. Freund and R. Schapire. Experiments with a new boosting algorithm. Thirteenth International Conference on Machine Learning, 1996.
12. J. H. Friedman. Flexible metric nearest neighbor classification. Technical Report, Department of Statistics, Stanford University, 1994.
13. L. K. Hansen and P. Salamon. Neural network ensembles. IEEE Transactions on Pattern Analysis and Machine Intelligence, 12:993-1001, 1990.
14. T. Hastie and R. Tibshirani. Discriminant adaptive nearest neighbor classification. IEEE Transactions on Pattern Analysis and Machine Intelligence, 18(6):607-615, 1996.
15. R. Kohavi and D. H. Wolpert. Bias plus variance decomposition for zero-one loss functions. Thirteen International Conference on Machine Learning, 1996.
16. D. D. Margineantu and T. Dietterich. Pruning adaptive boosting. Fourteenth International Conference on Machine Learning, 1997.
17. J. R. Quinlan. Bagging, boosting and C4.5. Fourteenth National Conference on Artificial Intelligence, 1996.