| Evaluation of the confusion matrix method in the validation of an automated system for measuring feeding behaviour of cattle S Ruuska, W Hämäläinen, S Kajava, M Mughal, P Matilainen, J Mononen Behavioural processes 148, 56-62, 2018 | 263 | 2018 |
| Comparison of machine learning methods for intelligent tutoring systems W Hämäläinen, M Vinni International conference on intelligent tutoring systems, 525-534, 2006 | 195 | 2006 |
| Classifiers for educational data mining W Hämäläinen, M Vinni Handbook of Educational Data Mining, Chapman & Hall/CRC Data Mining and …, 2011 | 145* | 2011 |
| Data mining in personalizing distance education courses W Hämäläinen, TH Laine, E Sutinen Data mining in e-learning, 157-171, 2006 | 108 | 2006 |
| Efficient discovery of statistically significant association rules W Hämäläinen, M Nykänen 2008 Eighth IEEE international conference on data mining, 203-212, 2008 | 80 | 2008 |
| Kingfisher: an efficient algorithm for searching for both positive and negative dependency rules with statistical significance measures W Hämäläinen Knowledge and information systems 32, 383-414, 2012 | 66 | 2012 |
| A tutorial on statistically sound pattern discovery W Hämäläinen, GI Webb Data Mining and Knowledge Discovery 32 (2), 325--377, 2019 | 60 | 2019 |
| Jerk-based feature extraction for robust activity recognition from acceleration data W Hamäläinen, M Järvinen, P Martiskainen, J Mononen 2011 11th International Conference on Intelligent Systems Design and …, 2011 | 58 | 2011 |
| StatApriori: an efficient algorithm for searching statistically significant association rules W Hämäläinen Knowledge and information systems 23, 373-399, 2010 | 55 | 2010 |
| Problem-based learning of theoretical computer science W Hamalainen 34th Annual Frontiers in Education, 2004. FIE 2004., S1H/1-S1H/6 Vol. 3, 2004 | 40 | 2004 |
| Problem-based learning of theoretical computer science W Hämäläinen Kolin kolistelut Koli Calling 2003, Proceedings of the Third Finnish/Baltic …, 2003 | 40 | 2003 |
| Efficient discovery of the top-k optimal dependency rules with Fisher's exact test of significance W Hamalainen 2010 IEEE International Conference on Data Mining, 196-205, 2010 | 33 | 2010 |
| Measuring behaviour accurately with instantaneous sampling: A new tool for selecting appropriate sampling intervals W Hämäläinen, S Ruuska, T Kokkonen, S Orkola, J Mononen Applied Animal Behaviour Science 180, 166-173, 2016 | 23 | 2016 |
| New upper bounds for tight and fast approximation of Fisher’s exact test in dependency rule mining W Hämäläinen Computational statistics & data analysis 93, 469-482, 2016 | 19 | 2016 |
| Metabolomics of synovial fluid and infrapatellar fat pad in patients with osteoarthritis or rheumatoid arthritis P Nieminen, W Hämäläinen, J Savinainen, M Lehtonen, S Lehtiniemi, ... Inflammation 45 (3), 1101-1117, 2022 | 16 | 2022 |
| Can stealing cows distort the results of feeding trials? An experiment for quantification and prevention of stealing feed by dairy cows from roughage intake control feeders S Ruuska, W Hämäläinen, A Sairanen, E Juutinen, L Tuomisto, ... Applied Animal Behaviour Science 159, 1-8, 2014 | 15 | 2014 |
| Class NP, NP-complete, and NP-hard problems W Hämäläinen Sort, 1-7, 2006 | 14 | 2006 |
| Evaluation of clustering methods for adaptive learning systems W Hämäläinen, V Kumpulainen, M Mozgovoy Artificial Intelligence Applications in Distance Education, 237-260, 2014 | 13 | 2014 |
| Efficient search for statistically significant dependency rules in binary data W Hämäläinen Helsingin yliopisto, 2010 | 12 | 2010 |
| Statistically sound pattern discovery. W Hämäläinen, GI Webb KDD, 1976, 2014 | 11 | 2014 |
Geoff WebbProfessor of Information Technology Research, Monash UniversityVahvistettu sähköpostiosoite verkkotunnuksessa monash.edu
