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A survey of variable selection methods and multiclass learningin bio informatics
Megha Purohit,  Shyamal Pandya
Feature selection based data mining methods is one of the most important research directions in the fields of machine learning in recent years. This paper presents a review of assorted feature selection methods named filter, wrapper and embedded and multiclass classifiers like support vector machines (SVM), decision tree, averaged perceptron and neural network. Additionally it conveys an assessment of classifiers for breast cancer dataset.
Keywords- Feature selection, Bio informatics, Machine learning, and Multiclass classification.
Unique Identification Number - IJEDR1601068Page Number(s) - 428-430Pubished in - Volume 4 | Issue 1 | February 2016DOI (Digital Object Identifier) -    Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
Megha Purohit,  Shyamal Pandya,   "A survey of variable selection methods and multiclass learningin bio informatics"
, International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.4, Issue 1, pp.428-430, February 2016, Available at :http://www.ijedr.org/papers/IJEDR1601068.pdf