Algorithms for Smart World Technologies

Chapter 10Prediction Algorithms

This chapter delves into a comprehensive collection of algorithms crucial for predictive modeling, a cornerstone in the development of intelligent systems across diverse application domains. These algorithms form the foundation for enabling systems to anticipate future outcomes, making them indispensable in fields ranging from finance and healthcare to robotics and natural language processing. The primary categories of algorithms explored within this chapter include:

• Regression Algorithms: These algorithms are designed to predict continuous values, such as stock prices, temperature, or the likelihood of a customer churning.
• Classification Algorithms: These algorithms focus on categorizing data into discrete classes or labels, such as identifying spam emails, diagnosing diseases, or classifying images.
• Unsupervised Algorithms: These algorithms uncover hidden patterns and structures within data without prior knowledge of the expected outcomes. They are used for tasks such as customer segmentation, anomaly detection, and dimensionality reduction.

The subsequent sections of this chapter will delve deeper into each of these algorithm categories, providing a detailed overview of their principles, methodologies, and practical applications.

10.1 Regression

10.1.1 Least Squares and Nearest-neighbor Methods

Why does a simple linear model result ...