Publikationen

8 Ergebnisse

Books and Chapters

Kranen P., Müller E., Assent I., Krieger R., Seidl T.:
Incremental Learning of Medical Data for Multi-Step Patient Health Classification
Plant C., Böhm C. (eds.): Database Technology for Life Sciences and Medicine, World Scientific Publishing S.321-344 (2010)
[World Scientific Publishing ]

Journal Articles (peer reviewed)

Bifet A., Holmes G., Pfahringer B., Kranen P., Kremer H., Jansen T., Seidl T.:
MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering
Journal of Machine Learning Research (JMLR) Workshop and Conference Proceedings, Volume 11: Workshop on Applications of Pattern Analysis S.44-50 (2010)
[www.pascal-network.org/wapa2010] [JMLR Proc. Vol. 11] [pdf]

Conference papers (peer reviewed)

Bifet A., Holmes G., Pfahringer B., Kranen P., Kremer H., Jansen T., Seidl T.:
MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering
Journal of Machine Learning Research (JMLR) Workshop and Conference Proceedings, Volume 11: Workshop on Applications of Pattern Analysis S.44-50 (2010)
[www.pascal-network.org/wapa2010] [JMLR Proc. Vol. 11] [pdf]
Kranen P., Günnemann S., Fries S., Seidl T.:
MC-Tree: Improving Bayesian Anytime Classification
Proc. of the 22nd International Conference on Scientific and Statistical Database Management (SSDBM 2010), Heidelberg, Germany, Springer LNCS S.252-269 (2010)
[SSDBM 2010] [DOI: 10.1007/978-3-642-13818-8_19]
Kranen P., Krieger R., Denker S., Seidl T.:
Bulk loading Hierarchical Mixture Models for Efficient Stream Classification
Proc. 14th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2010), Hyderabad, India. Springer LNAI S.325-334 (2010)
[PAKDD 2010] [DOI: 10.1007/978-3-642-13672-6_32]
Assent I., Kranen P., Baldauf C., Seidl T.:
Detecting Outliers on Arbitrary Data Streams using Anytime Approaches
International Workshop on Novel Data Stream Pattern Mining Techniques (StreamKDD 2010) in conjunction with 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2010), Washington, DC, USA S.10-16 (2010)
[StreamKDD 2010] [online proceedings]
Bifet A., Holmes G., Pfahringer B., Kranen P., Kremer H., Jansen T., Seidl T.:
MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering
Invited presentation at the International Workshop on Handling Concept Drift in Adaptive Information Systems in conjunction with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2010). S.3-16 (2010)
Kranen P., Kremer H., Jansen T., Seidl T., Bifet A., Holmes G., Pfahringer B.:
Clustering Performance on Evolving Data Streams: Assessing Algorithms and Evaluation Measures within MOA
Proc. IEEE International Conference on Data Mining (ICDM 2010), Sydney, Australia S.1400-1403 (2010) (Demo)
[ICDM 2010]
Kranen P., Kremer H., Jansen T., Seidl T., Bifet A., Holmes G., Pfahringer B.:
Benchmarking Stream Clustering Algorithms within the MOA Framework
16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2010), Washington, DC, USA (2010) 2010 KDD - MOA (demo).pdf(Demo)
[KDD 2010]