Eduardo R. Hruschka

Jonathan de Andrade Silva, Eduardo R. Hruschka: An experimental study on the use of nearest neighbor-based imputation algorithms for classification tasks. Data Knowl. Eng. 84: 47-58 (2013)

Thiago F. Covoes, Eduardo R. Hruschka, Joydeep Ghosh: A study of K-Means-based algorithms for constrained clustering. Intell. Data Anal. 17(3): 485-505 (2013)

Luís Filipe da Cruz Nassif, Eduardo R. Hruschka: Document Clustering for Forensic Analysis: An Approach for Improving Computer Inspection. IEEE Transactions on Information Forensics and Security 8(1): 46-54 (2013)

Thiago F. Covoes, Eduardo R. Hruschka, Joydeep Ghosh: Competitive Learning With Pairwise Constraints. IEEE Trans. Neural Netw. Learning Syst. 24(1): 164-169 (2013)

Ayan Acharya, Eduardo R. Hruschka, Joydeep Ghosh, Sreangsu Acharyya: Transfer Learning with Cluster Ensembles. Journal of Machine Learning Research - Proceedings Track 27: 123-132 (2012)

Luiz F. S. Coletta, Lucas Vendramin, Eduardo R. Hruschka, Ricardo J. G. B. Campello, Witold Pedrycz: Collaborative Fuzzy Clustering Algorithms: Some Refinements and Design Guidelines. IEEE T. Fuzzy Systems 20(3): 444-462 (2012)

Jorge Kanda, Carlos Soares, Eduardo R. Hruschka, André Carlos Ponce Leon Ferreira de Carvalho: A Meta-Learning Approach to Select Meta-Heuristics for the Traveling Salesman Problem Using MLP-Based Label Ranking. ICONIP (3) 2012: 488-495

Ricardo M. Marcacini, Eduardo R. Hruschka, Solange O. Rezende: On the Use of Consensus Clustering for Incremental Learning of Topic Hierarchies. SBIA 2012: 112-121

Davidson M. Sestaro, Thiago F. Covoes, Eduardo R. Hruschka: A Semi-supervised Approach to Estimate the Number of Clusters per Class. SBRN 2012: 73-78

Ayan Acharya, Eduardo R. Hruschka, Joydeep Ghosh: A Privacy-Aware Bayesian Approach for Combining Classifier and Cluster Ensembles. CoRR abs/1204.4521 (2012)

Ayan Acharya, Eduardo R. Hruschka, Joydeep Ghosh, Sreangsu Acharyya: An Optimization Framework for Semi-Supervised and Transfer Learning using Multiple Classifiers and Clusterers. CoRR abs/1206.0994 (2012)

Ayan Acharya, Eduardo R. Hruschka, Joydeep Ghosh, Badrul Sarwar, Jean-David Ruvini: Probabilistic Combination of Classifier and Cluster Ensembles for Non-transductive Learning. CoRR abs/1211.2304 (2012)

Murilo Coelho Naldi, Ricardo J. G. B. Campello, Eduardo R. Hruschka, André C. P. L. F. Carvalho: Efficiency issues of evolutionary k-means. Appl. Soft Comput. 11(2): 1938-1952 (2011)

Edimilson Batista dos Santos, Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken: Bayesian network classifiers: Beyond classification accuracy. Intell. Data Anal. 15(3): 279-298 (2011)

Jorge Kanda, André Carlos Ponce Leon Ferreira de Carvalho, Eduardo R. Hruschka, Carlos Soares: Selection of algorithms to solve traveling salesman problems using meta-learning. Int. J. Hybrid Intell. Syst. 8(3): 117-128 (2011)

Thiago F. Covoes, Eduardo R. Hruschka: Towards improving cluster-based feature selection with a simplified silhouette filter. Inf. Sci. 181(18): 3766-3782 (2011)

Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken: A Bayesian imputation method for a clustering genetic algorithm. J. Comput. Meth. in Science and Engineering 11(4): 173-183 (2011)

Lucas Vendramin, Ricardo José Gabrielli Barreto Campello, Luiz F. S. Coletta, Eduardo R. Hruschka: Distributed Fuzzy Clustering with Automatic Detection of the Number of Clusters. DCAI 2011: 133-140

Jonathan de Andrade Silva, Eduardo R. Hruschka: Extending k-Means-Based Algorithms for Evolving Data Streams with Variable Number of Clusters. ICMLA (2) 2011: 14-19

Thiago F. Covoes, Eduardo R. Hruschka: Splitting and Merging Gaussian Mixture Model Components: An Evolutionary Approach. ICMLA (1) 2011: 106-111

Luís Filipe da Cruz Nassif, Eduardo R. Hruschka: Document Clustering for Forensic Computing: An Approach for Improving Computer Inspection. ICMLA (1) 2011: 265-268

Jorge Kanda, André Carlos Ponce Leon Ferreira de Carvalho, Eduardo R. Hruschka, Carlos Soares: Using Meta-learning to Recommend Meta-heuristics for the Traveling Salesman Problem. ICMLA (1) 2011: 346-351

Ayan Acharya, Eduardo R. Hruschka, Joydeep Ghosh, Sreangsu Acharyya: C 3E: A Framework for Combining Ensembles of Classifiers and Clusterers. MCS 2011: 269-278

Ayan Acharya, Eduardo R. Hruschka, Joydeep Ghosh: A Privacy-Aware Bayesian Approach for Combining Classifier and Cluster Ensembles. SocialCom/PASSAT 2011: 1169-1172

Lucas Vendramin, Ricardo J. G. B. Campello, Eduardo R. Hruschka: Relative clustering validity criteria: A comparative overview. Statistical Analysis and Data Mining 3(4): 209-235 (2010)

Edimilson Batista dos Santos, Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken: A Distance-Based Mutation Operator for learning Bayesian Network structures using Evolutionary Algorithms. IEEE Congress on Evolutionary Computation 2010: 1-8

Luiz F. S. Coletta, Eduardo R. Hruschka, Thiago F. Covoes, Ricardo J. G. B. Campello: Fuzzy Clustering-Based Filter. IPMU (1) 2010: 406-415

Pablo A. Jaskowiak, Ricardo J. G. B. Campello, Thiago F. Covoes, Eduardo R. Hruschka: A Comparative Study on the Use of Correlation Coefficients for Redundant Feature Elimination. SBRN 2010: 13-18

Jorge Kanda, André Carlos Ponce Leon Ferreira de Carvalho, Eduardo R. Hruschka, Carlos Soares: Using Meta-learning to Classify Traveling Salesman Problems. SBRN 2010: 73-78

Ricardo J. G. B. Campello, Eduardo R. Hruschka, Vinicius S. Alves: On the efficiency of evolutionary fuzzy clustering. J. Heuristics 15(1): 43-75 (2009)

Ricardo José Gabrielli Barreto Campello, Eduardo R. Hruschka: On comparing two sequences of numbers and its applications to clustering analysis. Inf. Sci. 179(8): 1025-1039 (2009)

Eduardo R. Hruschka, Antonio J. T. Garcia, Estevam R. Hruschka Jr., Nelson F. F. Ebecken: On the influence of imputation in classification: practical issues. J. Exp. Theor. Artif. Intell. 21(1): 43-58 (2009)

Eduardo R. Hruschka, Ricardo José Gabrielli Barreto Campello, Alex Alves Freitas, André Carlos Ponce Leon Ferreira de Carvalho: A Survey of Evolutionary Algorithms for Clustering. IEEE Transactions on Systems, Man, and Cybernetics, Part C 39(2): 133-155 (2009)

Thiago F. Covoes, Eduardo R. Hruschka, Leandro Nunes de Castro, Átila M. Santos: A Cluster-Based Feature Selection Approach. HAIS 2009: 169-176

Jonathan de Andrade Silva, Eduardo R. Hruschka: An Evolutionary Algorithm for Missing Values Substitution in Classification Tasks. HAIS 2009: 195-202

Thiago F. Covoes, Eduardo R. Hruschka: An Experimental Study on Unsupervised Clustering-Based Feature Selection Methods. ISDA 2009: 993-1000

Jonathan de Andrade Silva, Eduardo R. Hruschka: EACImpute: An Evolutionary Algorithm for Clustering-Based Imputation. ISDA 2009: 1400-1406

Lucas Vendramin, Ricardo J. G. B. Campello, Eduardo R. Hruschka: On the Comparison of Relative Clustering Validity Criteria. SDM 2009: 733-744

Danilo Horta, Murilo Coelho Naldi, Ricardo José Gabrielli Barreto Campello, Eduardo R. Hruschka, André Carlos Ponce Leon Ferreira de Carvalho: Evolutionary Fuzzy Clustering: An Overview and Efficiency Issues. Foundations of Computational Intelligence (4) 2009: 167-195

Lucas Vendramin, Ricardo J. G. B. Campello, Eduardo R. Hruschka: A Robust Methodology for Comparing Performances of Clustering Validity Criteria. SBIA 2008: 237-247

Murilo Coelho Naldi, André Carlos Ponce Leon Ferreira de Carvalho, Ricardo José Gabrielli Barreto Campello, Eduardo R. Hruschka: Genetic Clustering for Data Mining. Soft Computing for Knowledge Discovery and Data Mining 2008: 113-132

Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken: Bayesian networks for imputation in classification problems. J. Intell. Inf. Syst. 29(3): 231-252 (2007)

Hermes Senger, Eduardo R. Hruschka, Fabrício Alves Barbosa da Silva, Liria Matsumoto Sato, Calebe De Paula Bianchini, Bruno F. Jerosch: Exploiting idle cycles to execute data mining applications on clusters of PCs. Journal of Systems and Software 80(5): 778-790 (2007)

Vinicius S. Alves, Ricardo J. G. B. Campello, Eduardo R. Hruschka: A Fuzzy Variant of an Evolutionary Algorithm for Clustering. FUZZ-IEEE 2007: 1-6

Ricardo J. G. B. Campello, Eduardo R. Hruschka: A fuzzy extension of the silhouette width criterion for cluster analysis. Fuzzy Sets and Systems 157(21): 2858-2875 (2006)

Eduardo R. Hruschka, Ricardo J. G. B. Campello, Leandro Nunes de Castro: Evolving clusters in gene-expression data. Inf. Sci. 176(13): 1898-1927 (2006)

Eduardo R. Hruschka, Estevam R. Hruschka Jr., Thiago F. Covoes, Nelson F. F. Ebecken: Bayesian Feature Selection for Clustering Problems. JIKM 5(4): 315-327 (2006)

André L. Vizine, Leandro Nunes de Castro, Eduardo R. Hruschka, Ricardo R. Gudwin: Towards Improving Clustering Ants: An Adaptive Ant Clustering Algorithm. Informatica (Slovenia) 29(2): 143-154 (2005)

Eduardo R. Hruschka, Thiago F. Covoes: Feature Selection for Cluster Analysis: an Approach Based on the Simplified Silhouette Criterion. CIMCA/IAWTIC 2005: 32-38

Eduardo R. Hruschka, Thiago F. Covoes, Estevam R. Hruschka Jr., Nelson F. F. Ebecken: Feature Selection for Clustering Problems: a Hybrid Algorithm that Iterates Between k-means and a Bayesian Filter. HIS 2005: 405-410

Antonio J. T. Garcia, Eduardo R. Hruschka: Naive Bayes as an Imputation Tool for Classification Problems. HIS 2005: 497-499

Eduardo R. Hruschka, Estevam R. Hruschka Jr., Nelson F. F. Ebecken: Missing Values Imputation for a Clustering Genetic Algorithm. ICNC (3) 2005: 245-254

Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken: Applying Bayesian Networks for Meteorological Data Mining. SGAI Conf. 2005: 122-133

Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken: Feature Selection by Bayesian Networks. Canadian Conference on AI 2004: 370-379

Eduardo R. Hruschka, Estevam R. Hruschka Jr., Nelson F. F. Ebecken: Towards Efficient Imputation by Nearest-Neighbors: A Clustering-Based Approach. Australian Conference on Artificial Intelligence 2004: 513-525

Fabrício Alves Barbosa da Silva, Sílvia Carvalho, Eduardo R. Hruschka: A Scheduling Algorithm for Running Bag-of-Tasks Data Mining Applications on the Grid. Euro-Par 2004: 254-262

Eduardo R. Hruschka, Ricardo J. G. B. Campello, Leandro Nunes de Castro: Improving the Efficiency of a Clustering Genetic Algorithm. IBERAMIA 2004: 861-870

Fabrício Alves Barbosa da Silva, Sílvia Carvalho, Hermes Senger, Eduardo R. Hruschka, Cléver Ricardo Guareis de Farias: Running Data Mining Applications on the Grid: A Bag-of-Tasks Approach. ICCSA (2) 2004: 168-177

Eduardo R. Hruschka, Leandro Nunes de Castro, Ricardo J. G. B. Campello: Evolutionary Algorithms for Clustering Gene-Expression Data. ICDM 2004: 403-406

Vahid Sherafat, Leandro Nunes de Castro, Eduardo R. Hruschka: TermitAnt: An Ant Clustering Algorithm Improved by Ideas from Termite Colonies. ICONIP 2004: 1088-1093

Hermes Senger, Eduardo R. Hruschka, Fabrício Alves Barbosa da Silva, Liria Matsumoto Sato, Calebe De Paula Bianchini, Marcelo D. Esperidiãao: Inhambu: Data Mining Using Idle Cycles in Clusters of PCs. NPC 2004: 213-220

Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken: A Feature Selection Bayesian Approach for Extracting Classification Rules with a Clustering Genetic Algorithm. Applied Artificial Intelligence 17(5-6): 489-506 (2003)

Eduardo R. Hruschka, Nelson F. F. Ebecken: A genetic algorithm for cluster analysis. Intell. Data Anal. 7(1): 15-25 (2003)

Eduardo R. Hruschka, Estevam R. Hruschka Jr., Nelson F. F. Ebecken: Evaluating a Nearest-Neighbor Method to Substitute Continuous Missing Values. Australian Conference on Artificial Intelligence 2003: 723-734

Eduardo R. Hruschka, Estevam R. Hruschka Jr., Nelson F. F. Ebecken: A Nearest-Neighbor Method as a Data Preparation Tool for a Clustering Genetic Algorithm. SBBD 2003: 319-327

Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken: A Data Preparation Bayesian Approach for a Clustering Genetic Algorithm. HIS 2002: 453-461

Eduardo R. Hruschka, Nelson F. F. Ebecken: A clustering algorithm for extracting rules from supervised neural network models in data mining tasks. Int. J. Comput. Syst. Signal 1(1): 17-29 (2000)

Eduardo R. Hruschka, Nelson F. F. Ebecken: Applying a Clustering Genetic Algorithm for Extracting Rules from a Supervised Neural Network. IJCNN (3) 2000: 407-412