Result 1 to 20 of 56 total
A survey on graphical methods for classification predictive performance evaluation (English)
IEEE Trans. Knowl. Data Eng. 23, No. 11, 1601-1618 (2011).
1
A simple approach to incorporate label dependency in multi-label classification. (English)
Sidorov, Grigori (ed.) et al., Advances in soft computing. 9th Mexican international conference on artificial intelligence, MICAI 2010, Pachuca, Mexico, November 8‒13, 2010. Proceedings, Part II. Berlin: Springer (ISBN 978-3-642-16772-0/pbk). Lecture Notes in Computer Science 6438. Lecture Notes in Artificial Intelligence, 33-43 (2010).
2
A simple approach to incorporate label dependency in multi-label classification (English)
MICAI (2), 33-43 (2010).
3
Data mining with imbalanced class distributions: concepts and methods (English)
IICAI, 359-376 (2009).
4
A hybrid wrapper/filter approach for feature subset selection. (English)
Electron. J. SADIO 8, No. 1, 12-24, electronic only (2008).
5
Missing value imputation using a semi-supervised rank aggregation approach. (English)
Zaverucha, Gerson (ed.) et al., Advances in artificial intelligence ‒ SBIA 2008. 19th Brazilian symposium on artificial intelligence, Salvador, Brazil, October 26‒30, 2008. Proceedings. Berlin: Springer (ISBN 978-3-540-88189-6/pbk). Lecture Notes in Computer Science 5249. Lecture Notes in Artificial Intelligence, 217-226 (2008).
6
Construction of an attribute-value representation for semi-structured medical findings knowledge extraction (English)
CLEI Electron. J. 11, No. 2 (2008).
7
A study with class imbalance and random sampling for a decision tree learning system (English)
IFIP AI, 131-140 (2008).
8
Missing value imputation using a semi-supervised rank aggregation approach (English)
SBIA, 217-226 (2008).
9
Fuzzy feature subset selection using the Wang \& mendel method (English)
HIS, 590-595 (2008).
10
Evolving sets of symbolic classifiers into a single symbolic classifier using genetic algorithms (English)
HIS, 525-530 (2008).
11
A fractal dimension based filter algorithm to select features for supervised learning. (English)
Sichman, Jaime Simão (ed.) et al., Advances in artificial intelligence ‒ IBERAMIA-SBIA 2006. 2nd international joint conference, 10th Ibero-American conference on AI, 18th Brazilian AI symposium, Ribeirão Preto, Brazil, October 23‒27, 2006. Proceedings. Berlin: Springer (ISBN 978-3-540-45462-5/pbk). Lecture Notes in Computer Science 4140. Lecture Notes in Artificial Intelligence, 278-288 (2006).
12
Constructing ensembles of symbolic classifiers. (English)
Int. J. Hybrid Intell. Syst. 3, No. 3, 159-167 (2006).
13
Constructing ensembles of symbolic classifiers. (English)
Int. J. Hybrid Intell. Syst. 3, No. 3, 159-167 (2006).
14
A comparison of methods for rule subset selection applied to associative classification (English)
Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial 10, No. 32, 29-35 (2006).
15
A simple evaluation model for feature subset selection algorithms (English)
Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial 10, No. 32, 9-17 (2006).
16
On the class distribution labelling step sensitivity of CO-TRAINING (English)
IFIP AI, 199-208 (2006).
17
A fractal dimension based filter algorithm to select features for supervised learning (English)
IBERAMIA-SBIA, 278-288 (2006).
18
A multi-objective evolutionary algorithm to build knowledge classification rules with specific properties (English)
HIS, 41 (2006).
19
Balancing strategies and class overlapping. (English)
Fazel Famili, A. (ed.) et al., Advances in intelligent data analysis VI. 6th international symposium on intelligent data analysis, IDA 2005, Madrid, Spain, September 8‒10, 2005. Proceedings. Berlin: Springer (ISBN 3-540-28795-7/pbk). Lecture Notes in Computer Science 3646, 24-35 (2005).
20
Result 1 to 20 of 56 total
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