Classification Models in Machine Learning Techniques

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Author(s): Amit Majumder (National Institute of Technology, Jamshedpur, India)
Copyright: 2024
Pages: 16
Source title: Machine Learning Algorithms Using Scikit and TensorFlow Environments
Source Author(s)/Editor(s): Puvvadi Baby Maruthi (Dayananda Sagar University, India), Smrity Prasad (Dayananda Sagar University, India)and Amit Kumar Tyagi ( National Institute of Fashion Technology, New Delhi, India)
DOI: 10.4018/978-1-6684-8531-6.ch001

Keywords: Engineering Science Reference / Knowledge Management and Library Science / Machine Learning / Systems and Software Engineering

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Abstract

Classification is the process of identifying, understanding, and grouping objects and ideas into specified categories. These pre-categorized training datasets are used by machine learning techniques to classify datasets into relevant and acceptable categories. Using the incoming training data, machine learning classifiers assess the chance or probability that the incoming data will fall into one of the established categories. One of categorization's most prominent applications is used by the largest email service providers of today: classifying emails as “spam” or “non-spam.” In essence, classification is a form of “pattern recognition.” Following the application of classification algorithms to the training data, the same pattern (similar number sequences, words, or attitudes, etc.) is found in future data sets. Classification falls within the category of supervised learning in the context of machine learning.

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