منابع مشابه
A Granular Computing Approach to Machine Learning
The key to granular computing is to make use of granules in problem solving. Classification is one of the well studied problems in machine learning and data mining as it involves of discovery knowledge from large databases. We presents a granular computing view to classification problems and propose a granular computing approach to classification in this paper. The ID3 [8] and PRISM [2] algorit...
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The problem of concept formation and learning is examined from the viewpoint of granular computing. Correspondences are drawn between granules and concepts, between granulations and classifications, and between relations over granules and relations over concepts. Two learning strategies are investigated. A global attribute-oriented strategy searches for a good partition of a universe of objects...
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With emergence of biomedical informatics, Web intelligence, and E-business, new challenges are coming for knowledge discovery and data mining modeling problems. In this dissertation work, a framework named Granular Support Vector Machines (GSVM) is proposed to systematically and formally combine statistical learning theory, granular computing theory and soft computing theory to address challeng...
متن کاملParallel Computing for Machine Learning
My name is Xinlei Pan. I am a first year graduate student in bioengineering department. I’m interested in machine learning and its application in biological data analysis. Typically examples include gene expression data analysis to construct gene regulatory network, EEG data analysis to study brain function, etc. For the machine learning part, I have a particular interest in probabilistic graph...
متن کاملGranular Computing Methods in Bioinformatics* Granular Computing Methods in Bioinformatics
Permission is granted to quote short excerpts and to reproduce figures and tables from this report, provided that the source of such material is fully acknowledged.
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ژورنال
عنوان ژورنال: Granular Computing
سال: 2018
ISSN: 2364-4966,2364-4974
DOI: 10.1007/s41066-018-00146-2