Search results for "C4.5 algorithm"

showing 3 items of 3 documents

A Windowing strategy for Distributed Data Mining optimized through GPUs

2017

Abstract This paper introduces an optimized Windowing based strategy for inducing decision trees in Distributed Data Mining scenarios. Windowing consists in selecting a sample of the available training examples (the window) to induce a decision tree with an usual algorithm, e.g., J48; finding instances not covered by this tree (counter examples) in the remaining training examples, adding them to the window to induce a new tree; and repeating until a termination criterion is met. In this way, the number of training examples required to induce the tree is reduced considerably, while maintaining the expected accuracy levels; which is paid in terms of time performance. Our proposed enhancements…

Computer sciencebusiness.industryMulti-agent systemDecision treeProcess (computing)Window (computing)02 engineering and technologyMachine learningcomputer.software_genreRandom forestTree (data structure)C4.5 algorithmArtificial Intelligence020204 information systemsSignal Processing0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligenceData miningbusinesscomputerSoftwarePattern Recognition Letters
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Non-Technological Aspects on Web Searching Success

2008

This paper studies the influence of social, cultural and emotional background of typical Web users into the web searching process. Several variables, describing such aspects, are represented and statistically analyzed with well known clustering and classifying algorithms such, as COBWEB, J48, Bayes classification, and Correspondence analysis. Results indicate that the efficiency of the complete process of Information Retrieval will not be fully understood without considering subjectivity and personality facts.

Web standardsBayes' theoremInformation retrievalC4.5 algorithmComputer scienceProcess (engineering)media_common.quotation_subjectPersonalityCluster analysisCorrespondence analysisCategory utilitymedia_common
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An Agents and Artifacts Approach to Distributed Data Mining

2013

This paper proposes a novel Distributed Data Mining (DDM) approach based on the Agents and Artifacts paradigm, as implemented in CArtAgO [9], where artifacts encapsulate data mining tools, inherited from Weka, that agents can use while engaged in collaborative, distributed learning processes. Target hypothesis are currently constrained to decision trees built with J48, but the approach is flexible enough to allow different kinds of learning models. The twofold contribution of this work includes: i) JaCA-DDM: an extensible tool implemented in the agent oriented programming language Jason [2] and CArtAgO [10,9] to experiment DDM agent-based approaches on different, well known training sets. A…

business.industryComputer scienceMulti-agent systemDecision treeCollaborative learningcomputer.software_genreMachine learningC4.5 algorithmData miningArtificial intelligencebusinesscomputerProtocol (object-oriented programming)Agent-oriented programmingCounterexample
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