T-SPPA: Trended statistical preprocessing algorithm

Communications in Computer and Information Science

Volumn 188 CCIS, Issue PART 1, 2011, Pages 118-131

  Silva, Tiago ^a   Dutra, Inês ^a  

^a UNIVERSITY OF PORTO   (Portugal)

Author keywords

Aggregation; Machine Learning; Preprocessing; Relational Learning; Statistics

Indexed keywords

FLAT FILES; LEARNING TASKS; PRE-PROCESSING ALGORITHMS; PRE-PROCESSING METHOD; PREPROCESSING; REAL WORLD DATA; RELATIONAL LEARNING; STATISTICAL RELATIONAL LEARNING;

DATA PROCESSING; INDUCTIVE LOGIC PROGRAMMING (ILP); LEARNING SYSTEMS;

LEARNING ALGORITHMS;

EID: 79960317068     PISSN: 18650929     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-22389-1_11     Document Type: Conference Paper

References (13)

1. Berthold, M.R., Cebron, N., Dill, F., Gabriel, T.R., Kötter, T., Meinl, T., Ohl, P., Sieb, C., Thiel, K., Wiswedel, B.: KNIME: The Konstanz Information Miner. In: Studies in Classification, Data Analysis, and Knowledge Organization (GfKL 2007), Springer, Heidelberg (2007)
2. Helge Toutenberg, C., Rao, R.: Linear Models - Least Squares and Alternatives, 2nd edn. Springer, Heidelberg (1999)
3. Debnath, G., Shusterman, A., Hansch, C., Debnath, A.K, Lopez de Compadre, R.L.: Structure-activity relationship of mutagenic aromatic and heteroaromatic nitro compounds. correlation with molecular orbital energies and hydrophobicity. Journal of medicinal chemistry 34(2), 786-797 (1991)
4. Getoor, L., Taskar, B.: Introduction to Statistical Relational Learning. MIT Press, Cambridge (2007)
5. Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The weka data mining software: an update. SIGKDD Explor. Newsl. 11 (November 2009)
6. Knobbe, A.J., de Haas, M., Siebes, A.: Propositionalisation and aggregates. In: De Raedt, L., Siebes, A. (eds.) PKDD 2001. LNCS (LNAI), vol. 2168, pp. 277-288. Springer, Heidelberg (2001)
7. Lavrac, N., Dzeroski, S.: Inductive Logic Programming: Techniques and Applications. chapter 11, Ellis Horwood, New York (1994)
8. Hunter, E.J., Ramig, L.O., Little,M.A., McSharry, P.: Suitability of dysphonia measurements for telemonitoring of parkinson's disease. IEEE Transactions on Biomedical Engineering (2008)
9. Mierswa, I., Wurst, M., Klinkenberg, R., Scholz, M., Euler, T.: Yale: Rapid prototyping for complex data mining tasks. In: Ungar, L., Craven, M., Gunopulos, D., Eliassi-Rad, T. (eds.) KDD 2006: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 935-940. ACM, New York (2006)
10. Theja, P.V.V.K., Vanajakshi, L.: Short term prediction of traffic parameters using support vector machines technique. In: 3rd International Conference on Emerging Trends in Engineering and Technology (ICETET) 2010, pp. 70-75 (2010)
11. Pintelas, P., Kotsiantis, S., Kanellopoulos, D.: Data preprocessing for supervised leaning. International Journal of Computer Science 1(2), 111-117 (2006)
12. Srinivasan, A.: The Aleph Manual (2001)
13. Witten, I.H., Frank, E.: Data Mining: Practical machine learning tools and techniques, 2nd edn. Morgan Kaufmann, San Francisco (2005)