Active learning algorithm by selecting the most possibly wrong-predicted instances

Jisuanji Yanjiu yu Fazhan/Computer Research and Development

Volumn 45, Issue 3, 2008, Pages 472-478

  Long, Jun ^a   Yin, Jianping ^a   Zhu, En ^a   Cai, Zhiping ^a  

^a NATIONAL UNIVERSITY OF DEFENSE TECHNOLOGY   (China)

Author keywords

Active learning; Halving model; Sample complex; Sampling; Version space

Indexed keywords

PROBABILITY; SAMPLING;

ACTIVE LEARNING ALGORITHM; HALVING MODEL; HYPOTHESIS; SAMPLE COMPLEX; TARGET ACCURACY; TARGET FUNCTION; THE MOST POSSIBLY WRONG PREDICTED INSTANCES; VERSION SPACE;

LEARNING ALGORITHMS;

EID: 43249096537     PISSN: 10001239     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (14)

1. M Seeger. Learning with labeled and unlabeled data [R]. Edinburgh University, Tech Rep, 2001
2. D D Lewis, W A Gale. A sequential algorithm for training text classifiers [C]. In: Proc of the 17th ACM Int'l Conf on Research and Development in Information Retrieval. Berlin: Springer, 1994
3. Gong Xiujun, Sun Jianping, Shi Zhongzhi. An active Bayesian network classifier [J]. Journal of Computer Research and Development, 2002, 39 (5): 574-579 (in Chinese)
4. H S Seung, M Opper, H Sompolinsky. Query by committee [C]. The 5th Workshop on Computational Learning Theory, San Mateo, CA, 1992
5. H T Nguyen, A Smeulders. Active learning using pre-clustering [C]. The 21th Int'l Conf on Machine Learning, Banff, CA, 2004
6. S Tong, D Koller. Support vector machine active learning with applications to text classification [J]. Journal of Machine Learning Research, 2001, 2: 45-66
7. G Schohn, D Cohn. Less is more: Active learning with support vector machines [C]. In: Proc of the 17th Int'l Conf on Machine Learning. San Francisco: Morgan Kaufmann, 2000
8. C Campbell, N Cristianini, A Smola. Query learning with large margin classifiers [C]. In: Proc of the 17th Int'l Conf on Machine Learning. San Francisco: Morgan Kaufmann, 2000
9. D A Cohn, Z Ghahramani, M I Jordan. Active learning with statistical models [J]. Journal of Artificial Intelligence research, 1996, 4: 129-145
10. N Roy, A McCallum. Toward optimal active learning through sampling estimation of error [C]. The 18th Int'l Conf on Machine Learning, San Francisco, CA, 2001
11. Y Freund, H S Seung, E Shamir, et al. Selective sampling using the query by committee algorithm [J]. Machine Learning, 1997, 28 (2-3): 133-168
12. A Asuncion, D J Newman. UCI machine learning repository [OL]. http://archive.ics.uci.edu/ml/, 2006
13. J S Simonoff. Analyzing Categorical Data [M]. Berlin: Springer-Verlag, 2003
14. Bruce, Bulloch. Agricultural Datasets [OL]. http://www.es.waikato.ac.n2/vml/weka/agridatasets-jar, 2006