Adaptive Learning for Data Mining Classification
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 1
Abstract
The classification of algorithm for dataset Recommendation should be appropriate as it is very important and beneficial task but it goes through some difficulties. As per No-Free-Lunch theorem, for different classification problem there is no best classifier to decide which learning algorithm suits best for which type data and domain is difficult. A type of recommending classification algorithm is affirmed, this paper is based on meta-features promising classifier one recommended by Meta learning. As per the characteristics of data the problem algorithm is selected by adaptive learning. In knowledge discovery process the selection of algorithm will be advantageous by adaptive learning. In these theory measures of recommendation parameter and knowledge base architecture of adaptive learning is discussed. Different classification algorithms are applied on the different dataset and problems. And also algorithms are recommended for the classifications.
Authors and Affiliations
Mahendra Divekar, Ajay Patil, Pooja Patil, Anita Saini, Prof. Avinash Devare
Keywords
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