On the Design of a Parallel Object-Oriented Data Mining Toolkit

Conference · Wed May 17 04:00:00 EDT 2000

OSTI ID:791750

Kamath, C ^[1]; Cantu-Paz, E

---

1. LLNL

As data mining techniques are applied to ever larger data sets, it is becoming clear that parallel processors will play an important role in reducing the turn around time for data analysis. In this paper, we describe the design of a parallel object-oriented toolkit for mining scientific data sets. After a brief discussion of our design goals, we describe our overall system design that uses data mining to find useful information in raw data in an iterative and interactive manner. Using decision trees as an example, we illustrate how the need to support flexibility and extensibility can make the parallel implementation of our algorithms very challenging. As this is work in progress, we also describe the solution approaches we are considering to address these challenges.

• Research Organization: Lawrence Livermore National Lab., CA (US)
• Sponsoring Organization: USDOE Office of Defense Programs (DP) (US)
• DOE Contract Number: W-7405-ENG-48
• OSTI ID: 791750
• Report Number(s): UCRL-JC-138973
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS
ALGORITHMS
DATA ANALYSIS
DESIGN
FLEXIBILITY
IMPLEMENTATION
MINING