2008 |
24 | EE | Estevam R. Hruschka Jr.,
Maria do Carmo Nicoletti,
Vilma A. de Oliveira,
Gláucia M. Bressan:
BayesRule: A Markov-Blanket based procedure for extracting a set of probabilistic rules from Bayesian classifiers.
Int. J. Hybrid Intell. Syst. 5(2): 83-96 (2008) |
23 | | Marcos Evandro Cintra,
Heloisa de Arruda Camargo,
Estevam R. Hruschka Jr.,
Maria do Carmo Nicoletti:
Automatic Construction of Fuzzy Rule Bases: a further Investigation into two Alternative Inductive Approaches.
J. UCS 14(15): 2456-2470 (2008) |
2007 |
22 | EE | Sebastian D. C. de O. Galvão,
Estevam R. Hruschka Jr.:
A Markov Blanket Based Strategy to Optimize the Induction of Bayesian Classifiers When Using Conditional Independence Learning Algorithms.
DaWaK 2007: 355-364 |
21 | EE | Diego P. Vivencio,
Estevam R. Hruschka Jr.,
Maria do Carmo Nicoletti,
Edimilson Batista dos Santos,
Sebastian D. C. de O. Galvão:
Feature-weighted k-Nearest Neighbor Classifier.
FOCI 2007: 481-486 |
20 | EE | Estevam R. Hruschka Jr.,
Heloisa de Arruda Camargo,
Marcos Evandro Cintra,
Maria do Carmo Nicoletti:
BayesFuzzy: Using a Bayesian Classifier to Induce a Fuzzy Rule Base.
FUZZ-IEEE 2007: 1-6 |
19 | EE | Estevam R. Hruschka Jr.,
Maria do Carmo Nicoletti,
Vilma A. de Oliveira,
Gláucia M. Bressan:
Markov-Blanket Based Strategy for Translating a Bayesian Classifier into a Reduced Set of Classification Rules.
HIS 2007: 192-197 |
18 | EE | Estevam R. Hruschka Jr.,
Edimilson Batista dos Santos,
Sebastian D. C. de O. Galvão:
Variable Ordering in the Conditional Independence Bayesian Classifier Induction Process: An Evolutionary Approach.
HIS 2007: 204-209 |
17 | EE | Edimilson Batista dos Santos,
Estevam R. Hruschka Jr.,
Maria do Carmo Nicoletti:
Conditional independence based learning of bayesian classifiers guided by a variable ordering genetic search.
IEEE Congress on Evolutionary Computation 2007: 1444-1449 |
16 | EE | Estevam R. Hruschka Jr.,
Nelson F. F. Ebecken:
Towards efficient variables ordering for Bayesian networks classifier.
Data Knowl. Eng. 63(2): 258-269 (2007) |
15 | EE | 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) |
14 | EE | Maria do Carmo Nicoletti,
Lucas Baggio Figueira,
Estevam R. Hruschka Jr.:
Transferring neural network based knowledge into an exemplar-based learner.
Neural Computing and Applications 16(3): 257-265 (2007) |
2006 |
13 | EE | João Roberto Bertini Jr.,
Maria do Carmo Nicoletti,
Estevam R. Hruschka Jr.,
Arthur Ramer:
Two Variants of the Constructive Neural Network Tiling Algorithm.
HIS 2006: 49 |
12 | EE | Edimilson Batista dos Santos,
Estevam R. Hruschka Jr.:
VOGA: Variable Ordering Genetic Algorithm for Learning Bayesian Classifiers.
HIS 2006: 56 |
11 | EE | 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) |
2005 |
10 | EE | Maria do Carmo Nicoletti,
Lucas Baggio Figueira,
Estevam R. Hruschka Jr.:
Initializing an Exemplar Based Learning Process from a RuleNet Network.
HIS 2005: 125-130 |
9 | EE | 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 |
8 | EE | Eduardo R. Hruschka,
Estevam R. Hruschka Jr.,
Nelson F. F. Ebecken:
Missing Values Imputation for a Clustering Genetic Algorithm.
ICNC (3) 2005: 245-254 |
2004 |
7 | EE | 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 |
6 | EE | Estevam R. Hruschka Jr.,
Eduardo R. Hruschka,
Nelson F. F. Ebecken:
Feature Selection by Bayesian Networks.
Canadian Conference on AI 2004: 370-379 |
2003 |
5 | EE | 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 |
4 | | 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 |
3 | EE | 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) |
2002 |
2 | | 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 |
1 | EE | Estevam R. Hruschka Jr.,
Nelson F. F. Ebecken:
Missing values prediction with K2.
Intell. Data Anal. 6(6): 557-566 (2002) |