Overview of Machine Learning Algorithms

Christo El Morr, Manar Jammal, Hossam Ali-Hassan and Walid El-Hallak ()
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Christo El Morr: York University
Manar Jammal: York University
Hossam Ali-Hassan: York University, Glendon Campus
Walid El-Hallak: Ontario Health

Chapter Chapter 3 in Machine Learning for Practical Decision Making, 2022, pp 61-115 from Springer

Abstract: Abstract Knowledge is an invaluable resource for almost all entities, be they firms, organizations, communities, or individuals. Knowledge needs to be captured, processed, and analyzed. Well-defined knowledge can be represented in an accurate manner, such as a mathematical formula or a certain set of rules [1]. Knowledge can also be modeled, where a model permits us to explain reality, classify objects, and predict a value (or if an event will occur) knowing its relationship to other known values. If our knowledge is not complete, then we can approximate reality by learning from previous experiences and predicting an outcome with a certain likelihood of accuracy. Alongside the representation of knowledge, we need to store on a computer a reasoning method, i.e., an algorithm (a series of steps to be followed) to process this knowledge to arrive at an outcome/output (e.g., a decision, classification, or diagnosis).

Date: 2022
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DOI: 10.1007/978-3-031-16990-8_3

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