EACImpute: An evolutionary algorithm for clustering-based imputation

ISDA 2009 - 9th International Conference on Intelligent Systems Design and Applications

Volumn , Issue , 2009, Pages 1400-1406

  De Andrade Silva, Jonathan ^a   Hruschka, Eduardo R ^a  

^a UNIVERSITY OF SÃO PAULO   (Brazil)

Author keywords

Classification; Imputation; Missing values

Indexed keywords

CLASSIFICATION BIAS; CLASSIFICATION TASKS; DATA SETS; EMPIRICAL RESULTS; EVOLUTIONARY ALGORITHM FOR CLUSTERING; IMPUTATION METHODS; MISSING VALUES; PREDICTION CAPABILITY;

CLUSTERING ALGORITHMS; INTELLIGENT SYSTEMS;

EVOLUTIONARY ALGORITHMS;

EID: 77949527529     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISDA.2009.86     Document Type: Conference Paper

References (14)

1. D. Pyle, Data Preparation for Data Mining (The Morgan Kaufmann Series in Data Management Systems). Morgan Kaufmann, 1999.
2. J. L. Schafer, Analysis of Incomplete Multivariate Data. CRC, 2000.
3. O. G. Troyanskaya, M. Cantor, G. Sherlock, P. O. Brown, T. Hastie, R. Tibshirani, D. Botstein, and R. B. Altman, "Missing value estimation methods for dna microarrays." Bioinformatics, vol. 17, no. 6, pp. 520-525, 2001.
4. K.-Y. Kim, B.-J. Kim, and G.-S. Yi, "Reuse of imputed data in microarray analysis increases imputation efficiency," BMC Bioinformatics, vol. 5, p. 160, 2004.
5. L. P. Bŕas and J. C. Menezes, "Improving cluster-based missing value estimation of dna microarray data," Biomolecular Engineering, vol. 24, pp. 273-282, 2007.
6. E. R. Hruschka, A. J. T. Garcia, E. R. H. Jr., and N. F. F. Ebecken, "On the influence of imputation in classification: practical issues," Journal of Experimental and Theoretical Artificial Intelligence, vol. 21, pp. 43-58, 2009.
7. J. de Andrade Silva and E. R. Hruschka, "An evolutionary algorithm for missing values substitution in classification tasks," in 4th International Conference on Hybrid Artificial Intelligence Systems (HAIS-09), ser. Lecture Notes in Artifi-cial Intelligence, vol. 5572. Berlin: Springer-Verlag, 2009, pp. 237-247.
8. E. R. Hruschka, E. R. H. Junior, and N. F. F. Ebecken, "Towards efficient imputation by nearest-neighbors: A clustering based approach," in 17th Australian Joint Conference on Artificial Intelligence (AI'04), ser. Lecture Notes in Artificial Intelligence, vol. 3339. Berlin: Springer-Verlag, 2004, pp. 513-525.
9. I. Kononenko and I. B. E. Roskar, "Experiments in automatic learning of medical diagnostic rules." Jozef Stefan Institute, Tech. Rep., 1984.
10. W. Pedrycz, Knowledge-Based Clustering: From Data to Information Granules. Wiley-Interscience, 2005.
11. E. R. Hruschka, R. J. G. B. Campello, and L. N. de Castro, "Evolving clusters in gene-expression data," Information Sciences, vol. 176, no. 13, pp. 1898-1927, 2006.
12. M. R. Anderberg, Cluster Analysis for Applications. New York: Academic Press, Inc., 1973.
13. I. H. Witten and E. Frank, Data Mining: Practical Machine Learning Tools and Techniques, 2nd ed. Morgan Kaufmann, 2005.
14. J. Demšar, "Statistical comparisons of classifiers over multiple data sets," Journal Machine Learning Research, vol. 7, pp. 1-30, 2006.