| C4. 5, class imbalance, and cost sensitivity: why under-sampling beats over-sampling C Drummond, RC Holte Workshop on learning from imbalanced datasets II 11 (1–8), 2003 | 1601 | 2003 |
| Cost curves: An improved method for visualizing classifier performance C Drummond, RC Holte Machine learning 65, 95-130, 2006 | 419 | 2006 |
| Replicability is not reproducibility: nor is it good science C Drummond Proceedings of the Evaluation Methods for Machine Learning Workshop at the …, 2009 | 366 | 2009 |
| Exploiting the cost (in) sensitivity of decision tree splitting criteria C Drummond, RC Holte ICML 1 (1), 2000 | 316 | 2000 |
| Explicitly representing expected cost: An alternative to ROC representation C Drummond, RC Holte Proceedings of the sixth ACM SIGKDD international conference on Knowledge …, 2000 | 289 | 2000 |
| Accelerating reinforcement learning by composing solutions of automatically identified subtasks C Drummond Journal of Artificial Intelligence Research 16, 59-104, 2002 | 101 | 2002 |
| Severe class imbalance: Why better algorithms aren’t the answer C Drummond, RC Holte European Conference on Machine Learning, 539-546, 2005 | 98 | 2005 |
| What ROC Curves Can't Do (and Cost Curves Can). C Drummond, RC Holte ROCAI, 19-26, 2004 | 77 | 2004 |
| Manifold-based synthetic oversampling with manifold conformance estimation C Bellinger, C Drummond, N Japkowicz Machine Learning 107, 605-637, 2018 | 69 | 2018 |
| Machine learning as an experimental science (revisited) C Drummond AAAI workshop on evaluation methods for machine learning, 1-5, 2006 | 58 | 2006 |
| A learning agent that assists the browsing of software libraries CG Drummond, D Ionescu, RC Holte IEEE Transactions on Software Engineering 26 (12), 1179-1196, 2000 | 51 | 2000 |
| Searching with abstractions: A unifying framework and new high-performance algorithm RC Holte, C Drummond, MB Perez, RM Zimmer, AJ MacDonald Proceedings of the biennial conference-Canadian society for computational …, 1994 | 47 | 1994 |
| Synthetic oversampling for advanced radioactive threat detection C Bellinger, N Japkowicz, C Drummond 2015 IEEE 14th international conference on machine learning and applications …, 2015 | 44 | 2015 |
| Beyond the boundaries of smote: A framework for manifold-based synthetically oversampling C Bellinger, C Drummond, N Japkowicz Machine Learning and Knowledge Discovery in Databases: European Conference …, 2016 | 42 | 2016 |
| Confusion matrix TR Shultz, SE Fahlman, S Craw, P Andritsos, P Tsaparas, R Silva, ... Encyclopedia of machine learning 61 (8), 209-209, 2011 | 42 | 2011 |
| A domain independent data mining methodology for prognostics S Létourneau, C Yang, C Drummond, E Scarlett, J Valdes, M Zaluski Proceedings of the 59th meeting of the society for machine failure …, 2005 | 38 | 2005 |
| Warning: statistical benchmarking is addictive. Kicking the habit in machine learning C Drummond, N Japkowicz Journal of Experimental & Theoretical Artificial Intelligence 22 (1), 67-80, 2010 | 36 | 2010 |
| A learning apprentice for browsing RC Holte AAAI Spring Symposium on Software Agents, 1994 | 33 | 1994 |
| Composing functions to speed up reinforcement learning in a changing world C Drummond European Conference on Machine Learning, 370-381, 1998 | 32 | 1998 |
| Reproducible research: a minority opinion C Drummond Journal of Experimental & Theoretical Artificial Intelligence 30 (1), 1-11, 2018 | 25 | 2018 |