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Renato Cordeiro de Amorim
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2020 – today
- 2024
- [j22]Andrei Rykov, Renato Cordeiro de Amorim, Vladimir Makarenkov, Boris G. Mirkin:
Inertia-Based Indices to Determine the Number of Clusters in K-Means: An Experimental Evaluation. IEEE Access 12: 11761-11773 (2024) - 2023
- [j21]Renato Cordeiro de Amorim:
On Sum-Free Subsets of Abelian Groups. Axioms 12(8): 724 (2023) - [j20]Renato Cordeiro de Amorim, Vladimir Makarenkov:
On k-means iterations and Gaussian clusters. Neurocomputing 553: 126547 (2023) - [j19]Stiphen Chowdhury, Na Helian, Renato Cordeiro de Amorim:
Feature weighting in DBSCAN using reverse nearest neighbours. Pattern Recognit. 137: 109314 (2023) - 2022
- [j18]Simon Harris, Renato Cordeiro de Amorim:
An Extensive Empirical Comparison of k-means Initialization Algorithms. IEEE Access 10: 58752-58768 (2022) - 2021
- [j17]Alberto José Benayas Álamos, Reyhaneh Hashempour, Damian Rumble, Shoaib Jameel, Renato Cordeiro de Amorim:
Unified Transformer Multi-Task Learning for Intent Classification With Entity Recognition. IEEE Access 9: 147306-147314 (2021) - [j16]Renato Cordeiro de Amorim, Vladimir Makarenkov:
Improving cluster recovery with feature rescaling factors. Appl. Intell. 51(8): 5759-5774 (2021) - [j15]Renato Cordeiro de Amorim, Carlos David Lopez Ruiz:
Identifying meaningful clusters in malware data. Expert Syst. Appl. 177: 114971 (2021) - 2020
- [j14]Renato Cordeiro de Amorim, Vladimir Makarenkov, Boris G. Mirkin:
Core Clustering as a Tool for Tackling Noise in Cluster Labels. J. Classif. 37(1): 143-157 (2020) - [i6]Renato Cordeiro de Amorim, Carlos David Lopez Ruiz:
Identifying meaningful clusters in malware data. CoRR abs/2008.01175 (2020) - [i5]Renato Cordeiro de Amorim, Vladimir Makarenkov:
Improving cluster recovery with feature rescaling factors. CoRR abs/2012.00477 (2020)
2010 – 2019
- 2019
- [j13]Renato Cordeiro de Amorim:
Unsupervised feature selection for large data sets. Pattern Recognit. Lett. 128: 183-189 (2019) - 2018
- [j12]Deepak Panday, Renato Cordeiro de Amorim, Peter C. R. Lane:
Feature weighting as a tool for unsupervised feature selection. Inf. Process. Lett. 129: 44-52 (2018) - [i4]Stiphen Chowdhury, Renato Cordeiro de Amorim:
An efficient density-based clustering algorithm using reverse nearest neighbour. CoRR abs/1811.07615 (2018) - 2017
- [j11]Renato Cordeiro de Amorim, Andrei Shestakov, Boris G. Mirkin, Vladimir Makarenkov:
The Minkowski central partition as a pointer to a suitable distance exponent and consensus partitioning. Pattern Recognit. 67: 62-72 (2017) - 2016
- [j10]Renato Cordeiro de Amorim:
A Survey on Feature Weighting Based K-Means Algorithms. J. Classif. 33(2): 210-242 (2016) - [j9]Renato Cordeiro de Amorim, Vladimir Makarenkov:
Applying subclustering and Lp distance in Weighted K-Means with distributed centroids. Neurocomputing 173: 700-707 (2016) - [j8]Renato Cordeiro de Amorim, Vladimir Makarenkov, Boris G. Mirkin:
A-Wardpβ: Effective hierarchical clustering using the Minkowski metric and a fast k-means initialisation. Inf. Sci. 370-371: 343-354 (2016) - [i3]Renato Cordeiro de Amorim:
A survey on feature weighting based K-Means algorithms. CoRR abs/1601.03483 (2016) - [i2]Renato Cordeiro de Amorim, Christian Hennig:
Recovering the number of clusters in data sets with noise features using feature rescaling factors. CoRR abs/1602.06989 (2016) - [i1]Renato Cordeiro de Amorim, Vladimir Makarenkov, Boris G. Mirkin:
A-Wardpβ: Effective hierarchical clustering using the Minkowski metric and a fast k -means initialisation. CoRR abs/1611.01060 (2016) - 2015
- [j7]Renato Cordeiro de Amorim:
Feature Relevance in Ward's Hierarchical Clustering Using the L p Norm. J. Classif. 32(1): 46-62 (2015) - [j6]Renato Cordeiro de Amorim, Christian Hennig:
Recovering the number of clusters in data sets with noise features using feature rescaling factors. Inf. Sci. 324: 126-145 (2015) - 2014
- [c7]Mohammad Puttaroo, Peter Komisarczuk, Renato Cordeiro de Amorim:
Challenges in developing Capture-HPC exclusion lists. SIN 2014: 334 - [c6]Marcos Zampieri, Renato Cordeiro de Amorim:
Between Sound and Spelling: Combining Phonetics and Clustering Algorithms to Improve Target Word Recovery. PolTAL 2014: 438-449 - [p2]Renato Cordeiro de Amorim, Peter Komisarczuk:
Partitional Clustering of Malware Using K-Means. Cyberpatterns 2014: 223-233 - 2013
- [c5]Renato Cordeiro de Amorim, Boris G. Mirkin:
A Clustering-Based Approach to Reduce Feature Redundancy. KICSS 2013: 465-475 - [c4]Renato Cordeiro de Amorim, Marcos Zampieri:
Effective Spell Checking Methods Using Clustering Algorithms. RANLP 2013: 172-178 - 2012
- [j5]Renato Cordeiro de Amorim, Boris G. Mirkin, John Q. Gan:
Anomalous pattern based clustering of mental tasks with subject independent learning - some preliminary results. Artif. Intell. Res. 1(1): 55-62 (2012) - [j4]Renato Cordeiro de Amorim, Boris G. Mirkin:
Minkowski metric, feature weighting and anomalous cluster initializing in K-Means clustering. Pattern Recognit. 45(3): 1061-1075 (2012) - [c3]Renato Cordeiro de Amorim, Trevor I. Fenner:
Weighting Features for Partition around Medoids Using the Minkowski Metric. IDA 2012: 35-44 - [c2]Renato Cordeiro de Amorim, Peter Komisarczuk:
On Initializations for the Minkowski Weighted K-Means. IDA 2012: 45-55 - [c1]Renato Cordeiro de Amorim:
An Empirical Evaluation of Different Initializations on the Number of K-Means Iterations. MICAI (1) 2012: 15-26
2000 – 2009
- 2009
- [j3]Stefan Wermter, Renato Cordeiro de Amorim:
Elden, L (2007). Matrix Methods in Data Mining and Pattern Recognition. Philadelphia (USA): Society for Industrial and Applied Mathematics. Cogn. Syst. Res. 10(4): 377-379 (2009) - [j2]Renato Cordeiro de Amorim:
Computational Methods of Feature Selection, Huan Liu, Hiroshi Motoda, CRC Press, Boca Raton, FL (2007), 440 pp, ISBN 978-1-58488-878-9. Inf. Process. Manag. 45(4): 490-493 (2009) - [j1]Renato Cordeiro de Amorim:
Pascal Poncelet, Florent Masseglia, Maguelonne Teisseire: Successes and New Directions in Data Mining. Inf. Retr. 12(4): 504-508 (2009) - [p1]Renato Cordeiro de Amorim:
An Adaptive Spell Checker Based on PS3M: Improving the Clusters of Replacement Words. Computer Recognition Systems 3 2009: 519-526
Coauthor Index
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