Various Classifiers Performance Based Machine Learning Methods
Pramoda Patro1, Krishna Kumar2, G. Suresh Kumar3
1Pramoda Patro, Department of Mathematics, Koneru Lakshmaiah Education Foundation, Vaddeswaram (Andhra Pradesh), India.
2Krishna Kumar, Department of Mathematics, MIT School of Engineering, MIT Art Design and Technology University, Loni Kalbhor Pune (Maharashtra), India.
3G. Suresh Kumar, Department of Mathematics, Koneru Lakshmaiah Education Foundation, Vaddeswaram (Andhra Pradesh), India.
Manuscript received on 25 November 2019 | Revised Manuscript received on 06 December 2019 | Manuscript Published on 16 December 2019 | PP: 305-310 | Volume-8 Issue-3S3 November 2019 | Retrieval Number: C10691183S319/2019©BEIESP | DOI: 10.35940/ijrte.C1069.1183S319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Classification is a form of data mining (regarding machine learning) approach that is helpful in the prediction of group membership for data instances, where the data input is used by the computer program for learning and thereafter this learning is used for classifying the fresh observation made. This data set might just be bi-class or it can be multi-class also. Few instances of the problems in classification include: speech identification, handwriting identification, bio metric detection, document classification etc. Many classification methods exist, which can be utilized for classification. In this research work, the fundamental classification approaches and few important kinds of classification approaches that include decision tree induction, Bayesian networks,k-nearest neighbor classifier and Support Vector Machines (SVM) and fuzzy learning classifiers with their merits, drawbacks, probable applications and challenges faced with the solution available. There are different problems that have an effect on the classification and prediction. The objective of this research work is to render an extensive review of various classification approaches in machine learning. At last, the future work intended on the best classification techniques for the input data are discussed.
Keywords: Classification, Data Instances, Classification Techniques, Weaknesses and Review.
Scope of the Article: Machine Learning