Inductive Logic Programming for Multiple-Part Data: Applications on Structure-Activity Relationship Studies
Author:
Affiliation:
1. The Institute of Scientific and Industrial Research, Osaka University
Publisher
Japanese Society for Artificial Intelligence
Subject
Artificial Intelligence,Software
Link
http://www.jstage.jst.go.jp/article/tjsai/20/3/20_3_159/_pdf
Reference16 articles.
1. [Chevaleyre 00] Chevaleyre, Y. and Zucker, J.-D.: Solving multiple-instance and multiple-part learning problems with decision trees and decision rules: Application to the mutagenesis problem, Technical report, LIP6-CNRS, University Paris VI (2000)
2. [Chevaleyre 01] Chevaleyre, Y. and Zucker, J.-D.: A Framework for Learning Rules from Multiple Instance Data, in Proc. 12th European Conf. on Machine Learning, Vol. 2167 of LNCS, pp. 49--60, Springer (2001)
3. Solving the multiple instance problem with axis-parallel rectangles
4. [Gärtner 02] Gärtner, T., Flach, P. A., Kowalczyk, A., and Smola, A. J.: Multi-Instance Kernels, in Proc. 19th International Conf. on Machine Learning, pp. 179--186, Morgan Kaufmann (2002)
5. Relating chemical activity to structure: An examination of ILP successes
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