| General and efficient multisplitting of numerical attributes T Elomaa, J Rousu Machine learning 36, 201-244, 1999 | 233 | 1999 |
| An analysis of reduced error pruning T Elomaa, M Kaariainen Journal of Artificial Intelligence Research 15, 163-187, 2001 | 178 | 2001 |
| Multi-target regression with rule ensembles. T Aho, B Ženko, S Džzeroski, T Elomaa, C Brodley Journal of Machine Learning Research 13 (8), 2012 | 122 | 2012 |
| Efficient Multisplitting Revisited: Optima-Preserving Elimination of Partition Candidates T Elomaa, J Rousu Data Mining and Knowledge Discovery 8, 97-126, 2004 | 68 | 2004 |
| In defense of C4. 5: Notes on learning one-level decision trees T Elomaa Machine Learning Proceedings 1994, 62-69, 1994 | 57 | 1994 |
| Flexible view recognition for indoor navigation based on Gabor filters and support vector machines I Autio, T Elomaa Pattern recognition 36 (12), 2769-2779, 2003 | 39 | 2003 |
| The biases of decision tree pruning strategies T Elomaa International Symposium on Intelligent Data Analysis, 63-74, 1999 | 35 | 1999 |
| Selective Rademacher penalization and reduced error pruning of decision trees M Kääriäinen, T Malinen, T Elomaa The Journal of Machine Learning Research 5, 1107-1126, 2004 | 33 | 2004 |
| Forecasting sales in industrial services: Modeling business potential with installed base information K Stormi, T Laine, P Suomala, T Elomaa Journal of Service Management 29 (2), 277-300, 2018 | 31 | 2018 |
| Covering analysis of the greedy algorithm for partial cover T Elomaa, J Kujala Algorithms and Applications: Essays Dedicated to Esko Ukkonen on the …, 2010 | 21 | 2010 |
| Progressive rademacher sampling T Elomaa, M Kääriäinen AAAI/IAAI, 140-145, 2002 | 21 | 2002 |
| A geometric approach to feature selection T Elomaa, E Ukkonen Machine Learning: ECML-94: European Conference on Machine Learning Catania …, 1994 | 21 | 1994 |
| A walk from 2-norm SVM to 1-norm SVM J Kujala, T Aho, T Elomaa 2009 Ninth IEEE International Conference on Data Mining, 836-841, 2009 | 20 | 2009 |
| Finding optimal multi-splits for numerical attributes in decision tree learning T Elomaa, J Rousu Technical Report NC-TR-96-041, Royal Holloway, University of London, 1996 …, 1996 | 20 | 1996 |
| Principles of Data Mining and Knowledge Discovery: 6th European Conference, PKDD 2002, Helsinki, Finland, August 19–23, 2002, Proceedings T Elomaa, H Mannila, H Toivonen Springer, 2003 | 19* | 2003 |
| On Autonomous k-Means Clustering T Elomaa, H Koivistoinen International Symposium on Methodologies for Intelligent Systems, 228-236, 2005 | 18 | 2005 |
| On lookahead heuristics in decision tree learning T Elomaa, T Malinen Foundations of Intelligent Systems: 14th International Symposium, ISMIS 2003 …, 2003 | 18 | 2003 |
| A voronoi diagram approach to autonomous clustering H Koivistoinen, M Ruuska, T Elomaa Discovery Science: 9th International Conference, DS 2006, Barcelona, Spain …, 2006 | 17 | 2006 |
| An experimental comparison of inducing decision trees and decision lists in noisy domains T Elomaa, N Holsti Proceedings of the Fourth European Working Session on Learning, Montpelier …, 1989 | 16 | 1989 |
| Integer linear programming-based scheduling for transport triggered architectures T Äijö, P Jääskeläinen, T Elomaa, H Kultala, J Takala ACM Transactions on Architecture and Code Optimization (TACO) 12 (4), 1-22, 2015 | 15 | 2015 |
