Open AccessAccuracy of Prediction by Machine Learning Algorithms
Author(s) -
U. Srinivasulu Reddy,
Damodar
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.f1371.0986s319
Subject(s) - machine learning , computer science , artificial intelligence , algorithm , interpretation (philosophy) , computational learning theory , base (topology) , online machine learning , unsupervised learning , mathematics , mathematical analysis , programming language
Over the past few decades, Machine Learning (ML) has evolved from the endeavor of few computer enthusiasts exploiting the possibility of computers learning to play games, and a part of Mathematics (Statistics) that seldom considered computational approaches, to an independent research discipline that has not only provided the necessary base for statistical-computational principles of learning procedures, but also has developed various algorithms that are regularly used for text interpretation, design recognition, and a many other commercial purposes and has led to a separate research interest in data mining to identify hidden regularities or irregularities in social data that growing by second. This paper efforts on explaining the concept and evolution of Machine Learning, some of the popular Machine Learning algorithms and try to compare three most popular algorithms based on some basic notions. Sentiment140 dataset was used and performance of each algorithm in terms of training time, prediction time and accuracy of prediction have been documented and compared.