C4.5: programs for machine learning
C4.5: programs for machine learning
Parallel Formulations of Decision-Tree Classification Algorithms
Data Mining and Knowledge Discovery
PQE2000: HPC Tools for Industrial Applications
IEEE Concurrency
SPRINT: A Scalable Parallel Classifier for Data Mining
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Mining of Association Rules in Very Large Databases: A Structured Parallel Approach
Euro-Par '99 Proceedings of the 5th International Euro-Par Conference on Parallel Processing
Parallel Induction Algorithms for Data Mining
IDA '97 Proceedings of the Second International Symposium on Advances in Intelligent Data Analysis, Reasoning about Data
Parallel Classification for Data Mining on Shared-Memory Multiprocessors
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
High-performance data mining with skeleton-based structured parallel programming
Parallel Computing - Parallel data-intensive algorithms and applications
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In this work we show the research track and the current results about the application of structured parallel programming tools to develop scalable data-mining applications. We discuss the exploitation of the divide and conquer nature of the well known C4.5 classification algorithm in spite of its in-core memory requirements. The opportunity of applying external memory techniques to manage the data is advocated. Current results of the experiments are reported.