In this chapter, we discovered regression analysis algorithms. This will benefit you in gaining an important skill for predictive data analysis. You have gained an understanding of concepts such as regression analysis, multicollinearity, dummy variables, regression evaluation measures, and logistic regression. The chapter started with simple linear and multiple regressions. After simple linear and multiple regressions, our main focus was on multicollinearity, model development, and model evaluation measures. In later sections, we focused on logistic regression, characteristics, types of regression, and its implementation.
The next chapter, Chapter 10, Supervised Learning – Classification Techniques, will focus on classification, its techniques, the train-test split strategy, and performance evaluation measures. In later sections, the focus will be on data splitting, the confusion matrix, and performance evaluation measures such as accuracy, precision, recall, F1-score...
