INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
There are varieties of data mining algorithms and techniques available for the extraction of hidden knowledge from large data base. Classification is one of the widely used techniques in data mining. Different machine learning algorithms have been proposed for data classification. Several base classifiers are combined by meta learner whose individual performances in some way contribute to the overall classification. The premise is that meta-learning enhances the data mining task with the ability to learn and adapt from previous experience. This paper comprises empirical evaluation on the performance of two meta learning approaches on several base learning algorithm.
Keywords:
Meta-learning, classification, meta-learner, base classifiers, data mining.
Cite Article:
"Meta learning and Base learning on various data sets, A Comparative Study", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.3, Issue 5, page no.15-17, May-2018, Available :http://www.ijnrd.org/papers/IJNRD1805003.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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