Machine Learning Models in Smart Cities – Data-Driven Perspective

Machine learning models can detect hidden trends and patterns in datasets, leading to valuable insights and data-driven decision-makers to improve general performance. However, it is also possible to scale up the machine learning algorithms by paralyzing such algorithms and using big data processing synchronically. The validation dataset is usually 20-25% of the original dataset, while the original dataset is considered as a massive dataset it would be 1% of the original size. The measurement or criteria for calculating error in classification and regression algorithms are discussed in the following. However, in some literature, the validation dataset and testing dataset are considered the same, and the original dataset is not divided into three phases to build a machine learning model. In this chapter, the most common supervised learning algorithms, classification, and regression are introduced.