Learning to Enumerate
The Learning to Enumerate problem is a new variant of the typical active learning problem. Our objective is to find data that satisfies arbitrary but fixed conditions, without using any prelabeled training data. The key aspect here is to query as few as possible non-target data. While typical active learning techniques try to keep the number of queried labels low they give no regards to the class these instances belong to. Since the aim of this problem is different from the common active learning problem, we started with applying uncertainty sampling as a base technique and evaluated the performance of three different base learner on 19 public datasets from the UCI Machine Learning Repository.
KeywordsActive learning Learning to enumerate Exploration vs. exploitation Epsilon-greedy
This research was supported by the Landesstiftung Baden-Württemberg (Baden-Württemberg-STIPENDIUM) and by MEXT Grant-in-Aid for Scientific Research on Innovative Areas.
- 1.Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., Duchesnay, E.: Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12, 2825–2830 (2011)MathSciNetMATHGoogle Scholar
- 3.Baba, Y., Kashima, H., Nohara, Y., Kai, E., Ghosh, P., Islam, R., Ahmed, A., Kuruda, M., Inoue, S., Hiramatsu, T., Kimura, M., Shimizu, S., Kobayashi, K., Tsuda, K., Sugiyama, M., Blondel, M., Ueda, N., Kitsuregawa, M., Nakashima, N.: Predictive approaches for low-cost preventive medicine program in developing countries. In: Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1681–1690. ACM (2015)Google Scholar
- 4.Kajino, H., Kishimoto, A., Botea, A., Daly, E., Kotoulas, S.: Active learning for multi-relational data construction. In: Proceedings of the 24th International Conference on World Wide Web, pp. 560–569. ACM (2015)Google Scholar
- 6.Scikit-Learn User Guide. http://scikit-learn.org/stable/user_guide.html
- 7.UC Irvine Machine Learning Repository. https://archive.ics.uci.edu/ml/index.html