Decision tree induction in high dimensional, hierarchically distributed databases

Proceedings of the 2005 SIAM International Conference on Data Mining, SDM 2005

Volumn , Issue , 2005, Pages 466-470

  Bar Or, Amir ^a   Schuster, Assaf ^a   Wolff, Ran ^a   Keren, Daniel ^b  

^a TECHNION ISRAEL INSTITUTE OF TECHNOLOGY   (Israel)

^b UNIVERSITY OF HAIFA   (Israel)

Author keywords

Classification; Data mining; Decision trees; Distributed algorithms; High dimension data

Indexed keywords

CLASSIFICATION (OF INFORMATION); COST REDUCTION; DATA MINING; DECISION TREES; DISTRIBUTED COMPUTER SYSTEMS; DISTRIBUTED DATABASE SYSTEMS; PARALLEL ALGORITHMS; PEER TO PEER NETWORKS; SPACE DIVISION MULTIPLE ACCESS; STATISTICAL TESTS;

COMMUNICATION BANDWIDTH; COMMUNICATION OVERHEADS; DECISION TREE INDUCTION; DECISION-TREE ALGORITHM; DISTRIBUTED DATABASE; HIGH-DIMENSION DATA; LARGE-SCALE DISTRIBUTED SYSTEM; PEER-TO-PEER DATABASE;

TREES (MATHEMATICS);

EID: 84880114535     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1137/1.9781611972757.42     Document Type: Conference Paper

References (13)

1. G. Greenspan and D. Geiger. Model-based inference of haplotype block variation. RECOMB, pages 131-137, 2003.
2. R. R. Hudson. Generating samples under a Wright-Fisher neutral model of genetic variation. Bioinfor-matics, 18:337-338, 2002.
3. E. B. Hunt, J. Marin, and P. T. Stone. Experiments in Induction. Academic Press, 1966.
4. R. Jin and G. Agrawal. Communication and memory efficient parallel decision tree construction. In Proc. of the 3rd (SDM), 2003.
5. M. V. Joshi, G. Karypis, and V. Kumar. A new scalable and efficient parallel classification algorithm for mining large datasets. In Proc. of International Parallel Processing Symposium, 1998.
6. M. Mehta, R. Agrawal, and J. Rissanen. SLIQ: A fast scalable classifier for data mining. In Proc. of the Fifth Int'l Conference on Extending Database Technology, Avignon, France, 1996.
7. J. R. Quinlan. Induction of decision trees. Machine Learning, 1:81-106, 1986.
8. Rajeev Rastogi and Kyuseok Shim. PUBLIC: A decision tree classifier that integrates building and pruning. Data Mining and Knowledge Discovery, 4(4):315-344, 2000.
9. N. J. Risch. Searching for genetic determinants in the new millennium. In Nature 405, pages 847-856, 2000.
10. J. C. Shafer, R. Agrawal, and M. Mehta. SPRINT: A scalable parallel classifier for data mining. In Proc. of the 22nd VLDB Conf., 1996.
11. A. Srivastava, E.-H. (S.) Han, V. Kumar, and V. Singh. Parallel formulations of decision-tree classification algorithms. Data Mining and Knowledge Discovery: An International Journal, 3:237-261, 1999.
12. W. Sthlinger, O. Hogl, H. Stoyan, and M. Muller. Intelligent data mining for medical quality management. In the Fifth Workshop on Intelligent Data Analysis in Medicine and Pharmacology (IDAMAP-2000), Workshop Notes of the 14th European Conference on Artificial Intelligence (ECAI-2000), pp. 55-67, 2000.
13. M. M. Wagner, J. M. Robinson, F.-C. Tsui, J. U. Espino, and W. R. Hogan. Design of a national retail data monitor for public health surveillance. Journal of the American Medical Informatics Association JAMIA, 10(5):409-418, Sep/Oct 2003.