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Classification Techniques

In: Data Science and Analytics for SMEs

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  • Afolabi Ibukun Tolulope

Abstract

In this chapter, even though there are several classification techniques, we will explore the popular ones used for classification in the business domain. In doing this, we will use the third business problem centered on customer loyalty using neural networks, classification trees, and random forest algorithms. In solving this problem, we are particular about how to get and retain more customers for our small business. We will also introduce some other classification-based techniques such as K-nearest neighbor and logistic regression. In using these techniques to solve the problem, we explain the fundamental concepts in the chosen algorithms and use them to demonstrate how these problem solving processes can be adopted in real business scenarios.

Suggested Citation

  • Afolabi Ibukun Tolulope, 2022. "Classification Techniques," Springer Books, in: Data Science and Analytics for SMEs, chapter 0, pages 155-197, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4842-8670-8_7
    DOI: 10.1007/978-1-4842-8670-8_7
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