| Year |
Citation |
Score |
| 2016 |
Santos EBd, Hruschka ER, Ebecken NFF. Score Metrics for Learning Bayesian Networks used as Fitness Function in a Genetic Algorithm Chembiochem. 1-8. DOI: 10.21528/Cbic2011-38.2 |
0.414 |
|
| 2016 |
Silva NFFd, Coletta LFS, Hruschka ER, Hruschka ER. Using unsupervised information to improve semi-supervised tweet sentiment classification Information Sciences. 355: 348-365. DOI: 10.1016/J.Ins.2016.02.002 |
0.468 |
|
| 2015 |
Mitchell T, Cohen W, Hruschka E, Talukdar P, Betteridge J, Carlson A, Dalvi B, Gardner M, Kisiel. B, Krishnamurthy J, Lao N, Mazaitis K, Mohamed T, Nakashole N, Platanios E, et al. Never-Ending Learning Proceedings of the National Conference On Artificial Intelligence. 3: 2302-2310. DOI: 10.1145/3191513 |
0.378 |
|
| 2014 |
Dos Santos EB, Ebecken NF, Hruschka ER, Elkamel A, Madhuranthakam CM. Bayesian classifiers applied to the Tennessee Eastman process. Risk Analysis : An Official Publication of the Society For Risk Analysis. 34: 485-97. PMID 24117732 DOI: 10.1111/Risa.12112 |
0.436 |
|
| 2014 |
Amaral LRD, Hruschka ER. Transgenic: An evolutionary algorithm operator Neurocomputing. 127: 104-113. DOI: 10.1016/J.Neucom.2013.08.037 |
0.357 |
|
| 2013 |
Nicoletti MC, Lisboa FOSS, Hruschka ER. Automatic Learning of Temporal Relations Under the Closed World Assumption Fundamenta Informaticae. 124: 133-151. DOI: 10.3233/Fi-2013-828 |
0.38 |
|
| 2013 |
Hruschka ER, Duarte MC, Nicoletti MC. Coupling as Strategy for Reducing Concept-Drift in Never-ending Learning Environments Fundamenta Informaticae. 124: 47-61. DOI: 10.3233/Fi-2013-824 |
0.44 |
|
| 2011 |
Hruschka ER, Hruschka ER, Ebecken NEF. A Bayesian imputation method for a clustering genetic algorithm Journal of Computational Methods in Sciences and Engineering Archive. 11: 173-183. DOI: 10.3233/Jcm-2011-0362 |
0.364 |
|
| 2009 |
Hruschka ER, Garcia AJT, Hruschka ER, Ebecken NFF. On the influence of imputation in classification: practical issues Journal of Experimental and Theoretical Artificial Intelligence. 21: 43-58. DOI: 10.1080/09528130802246602 |
0.359 |
|
| 2009 |
Bressan GM, Oliveira VA, Hruschka ER, Nicoletti MC. Using Bayesian networks with rule extraction to infer the risk of weed infestation in a corn-crop Engineering Applications of Artificial Intelligence. 22: 579-592. DOI: 10.1016/J.Engappai.2009.03.006 |
0.405 |
|
| 2007 |
Hruschka ER, Galvao SDCdO. Fast Conditional Independence-based Bayesian Classifier Journal of Computing Science and Engineering. 1: 162-176. DOI: 10.5626/Jcse.2007.1.2.162 |
0.476 |
|
| 2007 |
Nicoletti MdC, Figueira LB, Hruschka ER. Transferring neural network based knowledge into an exemplar-based learner Neural Computing and Applications. 16: 257-265. DOI: 10.1007/S00521-007-0088-8 |
0.434 |
|
| 2006 |
Hruschka ER, Hruschka ER, Covões TF, Ebecken NFF. Bayesian Feature Selection for Clustering Problems Journal of Information & Knowledge Management. 5: 315-327. DOI: 10.1142/S0219649206001578 |
0.431 |
|
| 2004 |
Hruschka ER, Hruschka ER, Ebecken NFF. Feature Selection by Bayesian Networks Lecture Notes in Computer Science. 370-379. DOI: 10.1007/978-3-540-24840-8_26 |
0.426 |
|
| 2003 |
Hruschka ER, Ebecken NFF. A feature selection Bayesian approach for a clustering genetic algorithm Wit Transactions On Information and Communication Technologies. 29. DOI: 10.2495/Data030181 |
0.415 |
|
| 2002 |
Hruschka ER, Ebecken NFF. Ordering attributes for missing values prediction and data classification Wit Transactions On Information and Communication Technologies. 28. DOI: 10.2495/Data020571 |
0.467 |
|
| Show low-probability matches. |