C4.5: programs for machine learning
C4.5: programs for machine learning
Introduction to parallel computing: design and analysis of algorithms
Introduction to parallel computing: design and analysis of algorithms
Experiments on multistrategy learning by meta-learning
CIKM '93 Proceedings of the second international conference on Information and knowledge management
Machine learning, neural and statistical classification
Machine learning, neural and statistical classification
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Use of Contextual Information for Feature Ranking and Discretization
IEEE Transactions on Knowledge and Data Engineering
Unstructured Tree Search on SIMD Parallel Computers
IEEE Transactions on Parallel and Distributed Systems
Database Mining: A Performance Perspective
IEEE Transactions on Knowledge and Data Engineering
SLIQ: A Fast Scalable Classifier for Data Mining
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
SPRINT: A Scalable Parallel Classifier for Data Mining
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
A One-Pass Algorithm for Accurately Estimating Quantiles for Disk-Resident Data
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Concatenated Parallelism: A Technique for Efficient Parallel Divide and Conquer
SPDP '96 Proceedings of the 8th IEEE Symposium on Parallel and Distributed Processing (SPDP '96)
ScalParC: A New Scalable and Efficient Parallel Classification Algorithm for Mining Large Datasets
IPPS '98 Proceedings of the 12th. International Parallel Processing Symposium on International Parallel Processing Symposium
High performance data mining (tutorial PM-3)
Tutorial notes of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Iceberg-cube computation with PC clusters
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Boosting Algorithms for Parallel and Distributed Learning
Distributed and Parallel Databases - Special issue: Parallel and distributed data mining
High-performance data mining with skeleton-based structured parallel programming
Parallel Computing - Parallel data-intensive algorithms and applications
IEEE Transactions on Knowledge and Data Engineering
Analysis and synthesis of agents that learn from distributed dynamic data sources
Emergent neural computational architectures based on neuroscience
Parallel Implementation of Decision Tree Learning Algorithms
EPIA '01 Proceedings of the10th Portuguese Conference on Artificial Intelligence on Progress in Artificial Intelligence, Knowledge Extraction, Multi-agent Systems, Logic Programming and Constraint Solving
Parallelisation of C4.5 as a Particular Divide and Conquer Computation
IPDPS '00 Proceedings of the 15 IPDPS 2000 Workshops on Parallel and Distributed Processing
Analysis and Synthesis of Agents That Learn from Distributed Dynamic Data Sources
Emergent Neural Computational Architectures Based on Neuroscience - Towards Neuroscience-Inspired Computing
Parallel and Distributed Data Mining: An Introduction
Revised Papers from Large-Scale Parallel Data Mining, Workshop on Large-Scale Parallel KDD Systems, SIGKDD
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
Handbook of data mining and knowledge discovery
Sourcebook of parallel computing
Hierarchical Decision Tree Induction in Distributed Genomic Databases
IEEE Transactions on Knowledge and Data Engineering
Parallel univariate decision trees
Pattern Recognition Letters
A Streaming Parallel Decision Tree Algorithm
The Journal of Machine Learning Research
VECPAR'02 Proceedings of the 5th international conference on High performance computing for computational science
Modeling of network computing systems for decision tree induction tasks
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
Parallel boosted regression trees for web search ranking
Proceedings of the 20th international conference on World wide web
ALT'05 Proceedings of the 16th international conference on Algorithmic Learning Theory
Parallel decision tree with application to water quality data analysis
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part II
Decision trees: a recent overview
Artificial Intelligence Review
The Journal of Supercomputing
A hybrid decision tree classifier
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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Classification decision tree algorithms are usedextensively for data mining in many domains such as retail targetmarketing, fraud detection, etc. Highly parallel algorithms forconstructing classification decision trees are desirable for dealingwith large data sets in reasonable amount of time. Algorithms forbuilding classification decision trees have a natural concurrency,but are difficult to parallelize due to the inherent dynamic natureof the computation. In this paper, we present parallel formulationsof classification decision tree learning algorithm based oninduction. We describe two basic parallel formulations. One isbased on Synchronous Tree Construction Approach and the otheris based on Partitioned Tree Construction Approach. We discussthe advantages and disadvantages of using these methods and propose ahybrid method that employs the good features of these methods. Wealso provide the analysis of the cost of computation andcommunication of the proposed hybrid method. Moreover, experimentalresults on an IBM SP-2 demonstrate excellent speedups andscalability.