Open AccessA Comparative Study on Supervised Machine Learning Algorithm
Author(s) -
Monica Gupta
Publication year - 2022
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2022.39980
Subject(s) - machine learning , computer science , artificial intelligence , naive bayes classifier , support vector machine , decision tree , random forest , task (project management) , carry (investment) , online machine learning , algorithm , active learning (machine learning) , management , finance , economics
Machine learning enables computers to act and make data driven decisions rather than being explicitly programmed to carry out a certain task. It is a tool and technology which can answer the question from your data. These programs are designed to learn and improve over time when exposed to new data. ML is a subset or a current application of AI. It is based on an idea that we should be able to give machines access to data and let them learn from themselves. ML deals with extraction of patterns from dataset, this means that machines can not only find the rules for optimal behavior but also can adapt to the changes in the world. Many of the algorithms involved have been known for decades. In this paper various algorithms of machine learning have been discussed. Machine learning algorithms are used for various purposes but we can say that once the machine learning algorithm studies how to manage data, it can do its work accordingly by itself. Keywords: Linear Regression, Logistic Regression, KNN, Naive Bayes, Decision Trees, SVM, Random Forest