Result 1 to 19 of 19 total
Online evaluation of email streaming classifiers using GNUsmail. (English)
Gama, João (ed.) et al., Advances in intelligent data analysis X. 10th international symposium, IDA 2011, Porto, Portugal, October 29‒31, 2011. Proceedings. Berlin: Springer (ISBN 978-3-642-24799-6/pbk). Lecture Notes in Computer Science 7014, 90-100 (2011).
1
Studying the hybridization of artificial neural networks in HECIC. (English)
Cabestany, Joan (ed.) et al., Advances in computational intelligence. 11th international work-conference on artificial neural networks, IWANN 2011, Torremolinos-Málaga, Spain, June 8‒10, 2011. Proceedings, Part II. Berlin: Springer (ISBN 978-3-642-21497-4/pbk). Lecture Notes in Computer Science 6692, 137-144 (2011).
2
Feature extraction for multi-label learning in the domain of email classification (English)
CIDM, 30-36 (2011).
3
Online evaluation of email streaming classifiers using gnusmail (English)
IDA, 90-100 (2011).
4
Studying the hybridization of artificial neural networks in HECIC (English)
IWANN (2), 137-144 (2011).
5
GNUsmail: open framework for on-line email classification. (English)
Coelho, Helder (ed.) et al., ECAI 2010. 19th European conference on artificial intelligence, August 16‒20, 2010 Lisbon, Portugal. Including proceedings of the 6th prestigious applications of artificial intelligence (PAIS-2010). Amsterdam: IOS Press (ISBN 978-1-60750-605-8/pbk; 978-1-60750-606-5/ebook). Frontiers in Artificial Intelligence and Applications 215, 1141-1142 (2010).
6
Gnusmail: open framework for on-line email classification (English)
ECAI, 1141-1142 (2010).
7
Hybridizing ensemble classifiers with individual classifiers (English)
ISDA, 199-202 (2009).
8
Improving the performance of an incremental algorithm driven by error margins. (English)
Intell. Data Anal. 12, No. 3, 305-318 (2008).
9
Incremental learning with multiple classifier systems using correction filters for classification. (English)
Berthold, Michael R. (ed.) et al., Advances in intelligent data analysis VII. 7th international symposium on intelligent data analysis, IDA 2007, Ljubljana, Slovenia, September 6‒8, 2007. Proceedings. Berlin: Springer (ISBN 978-3-540-74824-3/pbk). Lecture Notes in Computer Science 4723, 106-117 (2007).
10
Incremental learning with multiple classifier systems using correction filters for classification (English)
IDA, 106-117 (2007).
11
Incremental algorithm driven by error margins. (English)
Todorovski, Ljupčo (ed.) et al., Discovery science. 9th international conference, DS 2006, Barcelona, Spain, October 7‒10, 2006. Proceedings. Berlin: Springer (ISBN 978-3-540-46491-4/pbk). Lecture Notes in Computer Science 4265. Lecture Notes in Artificial Intelligence, 358-362 (2006).
12
FE-CIDIM: fast ensemble of CIDIM classifiers. (English)
Int. J. Syst. Sci. 37, No. 13, 939-947 (2006).
13
Multiple classifier systems and layered learning based on CIDIM (English)
Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial 10, No. 29, 49-58 (2006).
14
Incremental algorithm driven by error margins (English)
Discovery Science, 358-362 (2006).
15
ML-CIDIM: Multiple layers of multiple classifier systems based on CIDIM. (English)
Ślȩzak, Dominik (ed.) et al., Rough sets, fuzzy sets, data mining, and granular computing. 10th international conference, RSFDGrC 2005, Regina, Canada, August 31 ‒ September 3, 2005. Proceedings, Part II. Berlin: Springer (ISBN 3-540-28660-8/pbk). Lecture Notes in Computer Science 3642. Lecture Notes in Artificial Intelligence, 138-146 (2005).
16
ML-CIDIM: multiple layers of multiple classifier systems based on CIDIM (English)
RSFDGrC (2), 138-146 (2005).
17
E-CIDIM: ensemble of CIDIM classifiers (English)
ADMA, 108-117 (2005).
18
Induction of decision trees using an internal control of induction (English)
IWANN, 795-803 (2005).
19
Result 1 to 19 of 19 total
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