Recovering the number of clusters in data sets with noise features using feature rescaling factors RC De Amorim, C Hennig Information sciences 324, 126-145, 2015 | 422 | 2015 |
Minkowski metric, feature weighting and anomalous cluster initializing in K-Means clustering RC de Amorim, B Mirkin Pattern Recognition 45 (3), 1061–1075, 2012 | 421 | 2012 |
Feature relevance in Ward’s hierarchical clustering using the Lp norm R Cordeiro de Amorim Journal of Classification 32 (1), 46-62, 2015 | 96 | 2015 |
A survey on feature weighting based K-Means algorithms RC de Amorim Journal of Classification 33 (2), 210-242, 2016 | 86 | 2016 |
Feature weighting as a tool for unsupervised feature selection D Panday, RC De Amorim, P Lane Information processing letters 129, 44-52, 2018 | 55 | 2018 |
Effective Spell Checking Methods Using Clustering Algorithms RC de Amorim, M Zampieri Recent Advances in Natural Language Processing, 172-178, 2013 | 45 | 2013 |
Constrained Clustering with Minkowski Weighted K-Means RC de Amorim Proceedings of the 13th IEEE International Symposium on Computational …, 2012 | 44 | 2012 |
Applying subclustering and L p distance in Weighted K-Means with distributed centroids RC de Amorim, V Makarenkov Neurocomputing 173 (3), 700--707, 2016 | 43 | 2016 |
On Initializations for the Minkowski Weighted K-Means RC de Amorim, P Komisarczuk Lecture Notes in Computer Science, 45--55, 2012 | 36 | 2012 |
A-Wardpβ: Effective hierarchical clustering using the Minkowski metric and a fast k-means initialisation RC De Amorim, V Makarenkov, B Mirkin Information Sciences 370, 343-354, 2016 | 28 | 2016 |
Constrained Intelligent K-Means: Improving Results with Limited Previous Knowledge. RC de Amorim The Second International Conference on Advanced Engineering Computing and …, 2008 | 27 | 2008 |
Unsupervised feature selection for large data sets RC de Amorim Pattern Recognition Letters 128, 183-189, 2019 | 20 | 2019 |
An Empirical Evaluation of Different Initializations on the Number of K-means Iterations RC de Amorim Lecture Notes in Computer Science 7629, 15-26, 2013 | 20 | 2013 |
The Minkowski central partition as a pointer to a suitable distance exponent and consensus partitioning RC De Amorim, A Shestakov, B Mirkin, V Makarenkov Pattern Recognition 67, 62-72, 2017 | 19 | 2017 |
Between Sound and Spelling: Combining Phonetics and Clustering Algorithms to Improve Target Word Recovery M Zampieri, RC de Amorim Proceedings of the 9th International Conference on Natural Language Processing, 2014 | 16 | 2014 |
On partitional clustering of malware RC de Amorim, P Komisarczuk The First International Workshop on Cyber Patterns: Unifying Design Patterns …, 2012 | 13* | 2012 |
Weighting features for Partition Around Medoids using the Minkowski metric RC de Amorim, T Fenner Lecture Notes in Computer Science, 35--44, 2012 | 13 | 2012 |
Learning feature weights for K-Means clustering using the Minkowski metric RC de Amorim Birkbeck, University of London, 2011 | 12 | 2011 |
Feature weighting and anomalous cluster initializing in k-means clustering RC Amorim, B Mirkin, M Metric Pattern Recognition 45 (3), 1061-1075, 2012 | 11 | 2012 |
Challenges in developing capture-hpc exclusion lists M Puttaroo, P Komisarczuk, RC De Amorim Proceedings of the 7th International Conference on Security of Information …, 2014 | 9 | 2014 |