An Overview of Supervised Machine Learning Paradigms and their Classifiers (original) (raw)

A review on Machine Learning: Application and Algorithms by Diksha, Pallavi and Pankaj Verma

IJRES, 2022

The field of machine learning is introduced at a conceptual level. The main goal of machine learning is how computers automatically learn without any human invention or assistance so that they can adjust their action accordingly. We are discussing mainly three types of algorithms in machine learning and also discussed ML's features and applications in detail. Supervised ML, In this typeof algorithm, the machine applies what it has learned in its past to new data, in which they use labeled examples, so that they predict future events. Unsupervised ML studies how systems can infer a function, so that they can describe a hidden structure from unlabeled data. Reinforcement ML, is a type of learning method, which interacts with its environment, produces action, as well as discovers errors and rewards.

A Comparative Study on Supervised Machine Learning Algorithm

International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2022

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.

Conceptual Review on Machine Learning Algorithms for Classification Techniques

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2021

Machine leaning is a ground of recent research that officially focuses on the theory, performance, and properties of learning systems and algorithms. It is a extremely interdisciplinary field building upon ideas from many different kinds of fields such as artificial intelligence, optimization theory, information theory, statistics, cognitive science, optimal control, and many other disciplines of science, engineering, and mathematics. Because of its implementation in a wide range of applications, machine learning has covered almost every scientific domain, which has brought great impact on the science and society. It has been used on a variety of problems, including recommendation engines, recognition systems, informatics and data mining, and autonomous control systems. This research paper compared different machine algorithms for classification. Classification is used when the desired output is a discrete label.

Thesis on Machine Learning Methods and Its Applications

IJRASET, 2021

In the 1950s, the concept of machine learning was discovered and developed as a subfield of artificial intelligence. However, there were no significant developments or research on it until this decade. Typically, this field of study has developed and expanded since the 1990s. It is a field that will continue to develop in the future due to the difficulty of analysing and processing data as the number of records and documents increases. Due to the increasing data, machine learning focuses on finding the best model for the new data that takes into account all the previous data. Therefore, machine learning research will continue in correlation with this increasing data. This research focuses on the history of machine learning, the methods of machine learning, its applications, and the research that has been conducted on this topic. Our study aims to give researchers a deeper understanding of machine learning, an area of research that is becoming much more popular today, and its applications.

A Simplistic Overview of Machine Learning

International Journal of Scientific Research in Science, Engineering and Technology, 2021

While dealing with machine learning, a computer learns first to perform a roles/task by learning a set of training examples. The computer performs then the same task along with data it hasn't found before. This paper presents a brief overview of machine-learning types along with instances. The paper also covers differences between supervised and unsupervised learning.

MACHINE LEARNING: A SURVEY

Machine learning [1], a branch of artificial intelligence, that gives computers the ability to learn without being explicitly programmed, means it gives system the ability to learn from data. There are two types of learning techniques: supervised learning and unsupervised learning [2]. This paper summarizes the recent trends of machine learning research.

Machine Learning & Associated Algorithms -A Review

Journal of Advances in Mathematical & Computational Science. Vol 10, No.3. Pp 1 – 14., 2022

Machine learning and associated algorithms occupies a pride of place in the execution of automation in the field of computing and its application to addressing contemporary and human-centred problems such as predictions, evaluations, deductions, analytics and analysis. This paper presents types of data and machine learning algorithms in a broader sense. We briefly discuss and explain different machine learning algorithms and real-world application areas based on machine learning. We highlight several research issues and potential future directions