Numerical Machine Learning

Logistic Regression

Author(s): Zhiyuan Wang*, Sayed Ameenuddin Irfan*, Christopher Teoh* and Priyanka Hriday Bhoyar *

Pp: 71-96 (26)

DOI: 10.2174/9789815136982123010005

* (Excluding Mailing and Handling)


This chapter delves into logistic regression, a widely used machine learning algorithm for classification tasks, with a focus on maintaining accessibility by minimizing abstract mathematical concepts. We present a concrete numerical example employing a small dataset to predict the ease of selling houses in the property market, guiding readers through each step of the process. Additionally, we supply sample codes and draw comparisons with the logistic regression model available in the scikit-learn library. Upon completion of this chapter, readers will have gained a comprehensive understanding of the inner workings of logistic regression, its relationship to algorithm implementation and performance, and the knowledge necessary to apply it to practical applications. 

Keywords: Logistic Regression, Classification, Numerical Example, Small Dataset, Scikit-Learn

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