Data Visualization in Large Scale Based on Trained Data

Abstract

Data visualization is one of the techniques to understand the patterns of data in graphical methods. Data visualization is an effective tool for transforming raw data into actionable insights and facilitating data-driven decision-making. High-dimensional synthetic data are datasets created artificially with an abundance of attributes or aspects. This type of synthetic data is particularly helpful for attempting to assess machine learning algorithms and data analysis techniques in scenarios with a large number of factors. The method can be difficult because of the more complicated nature of high-dimensional data, but it is necessary for a variety of applications, such as testing machine learning algorithms, evaluating data analysis techniques, and exploring model behaviour in high-dimensional spaces. These trained high-dimensional synthetic data are given to the visualization techniques to produce graphical representation and better decision-making models. This chapter elaborates on visualizing synthetic high-dimensional data for better understanding by common men.