Vol. 17 / 2022 – International Conference on Virtual Learning

Supervised Machine Learning: A Brief Introduction

Seemant TIWARI


Machine learning is being employed more and more in psychological research, and it can enhance our knowledge of how to categorise, anticipate, and treat psychosomatic illnesses and the negative health effects that go along with them. Machine learning provides new resources to address problems for which conventional statistical techniques are inadequate. One of the jobs that intelligent algorithms perform most commonly is supervised classification. The most accurate prediction algorithm is determined according to the data set, the number of situations, and the parameters. This article discusses numerous Supervised Machine Learning (ML) different classifiers, equates numerous supervised learning algorithms, and specifies the most effective classification method. This article offers a broad overview of machine learning with a particular emphasis on supervised learning. We present several popular supervised learning techniques. Therefore, we can argue that supervised predictive machine learning needs machine learning procedures that are detailed, correct, and have a low mistake percentage.

Machine learning, Classifiers, Data mining methods, Supervised machine learning

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Seemant TIWARI, "Supervised Machine Learning: A Brief Introduction", International Conference on Virtual Learning, ISSN 2971-9291, ISSN-L 1844-8933, vol. 17, pp. 219-230, 2022. https://doi.org/10.58503/icvl-v17y202218