Research outputs per year
Research outputs per year
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Dive into the research topics where Max Bramer is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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A rule-based classifier with accurate and fast rule term induction for continuous attributes
Almutairi, M., Stahl, F. & Bramer, M., 17 Jan 2019, Proceedings - 17th IEEE International Conference on Machine Learning and Applications, ICMLA 2018. Wani, M. A., Sayed-Mouchaweh, M., Lughofer, E., Gama, J. & Kantardzic, M. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 413-420 8 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open AccessFile226 Downloads (Pure) -
Improving modular classification rule induction with G-Prism using dynamic rule term boundaries
Almutairi, M., Stahl, F. & Bramer, M., Nov 2017, Artificial Intelligence XXXIV: 37th SGAI International Conference on Artificial Intelligence, AI 2017, Cambridge, UK, December 12-14, 2017, Proceedings. Bramer, M. & Petridis, M. (eds.). Springer, p. 115-128 (Lecture Notes in Computer Science; vol. 10630).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open AccessFile118 Downloads (Pure) -
Scaling up data mining techniques to large datasets using parallel and distributed processing
Stahl, F., Gaber, M. & Bramer, M., 2013, Business Intelligence and Performance Management: Theory, Systems, and Industrial Applications. Rausch, P., Sheta, A. & Ayesh, A. (eds.). Berlin: Springer, p. 243-262 20 p.Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review
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Homogeneous and heterogeneous distributed classification for pocket data mining
Stahl, F., Gaber, M., Aldridge, P., May, D., Liu, H., Bramer, M. & Yu, P., 2012, Transactions on large-scale data and knowledge-centered systems V. Hameurlain, A., Kung, J. & Wagner, R. (eds.). 7100 ed. Berlin: Springer, Vol. 5. p. 183-205 23 p. (Lecture notes in computer sciences; no. 7100).Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review
File137 Downloads (Pure) -
Jmax-pruning: a facility for the information theoretic pruning of modular classification rules
Stahl, F. & Bramer, M., 2012, In: Knowledge-Based Systems. 29, p. 12-19 8 p.Research output: Contribution to journal › Article › peer-review
File131 Downloads (Pure)