An Analytical Study on Machine Learning Techniques

Author:

Singh Law Kumar1ORCID,Pooja 1,Garg Hitendra2,Khanna Munish3,Bhadoria Robin Singh4ORCID

Affiliation:

1. Sharda University, India

2. GLA University, India

3. Hindustan College of Science and Technology, India

4. Birla Institute of Applied Sciences (BIAS), Bhimtal, India

Abstract

The last few months have produced a remarkable expansion in research and deep study in the field of machine learning. Machine learning is a technique in which the set of the methods are used by the computers to make prediction, improve prediction and behavior prediction based on dataset. The learning techniques can be classified as supervised and unsupervised learning. The focus is on supervised machine learning that covers all the predictions problem for which we had the dataset in which the outcome is already known. Some of the algorithm like naive bayes, linear regression, SVM, k-nearest neighbor, especially neural network have gain growth in this area. The classifiers of machine learning are completely unconstrained with the assumptions of statistical and for that they are adapted by complex data. The authors have demonstrated the application of machine learning techniques and its ethical issues.

Publisher

IGI Global

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