IJ
IJCRM
International Journal of Contemporary Research in Multidisciplinary
ISSN: 2583-7397
Open Access • Peer Reviewed
Impact Factor: 5.67

International Journal of Contemporary Research In Multidisciplinary, 2026;5(2):212-219

Compact Data Visualization for Feature Relationships and Class Separability

Author Name: Shridhar B. Dandin;   Santosh Kumar Das;   Megha Sinha;  

1. Department of Computer Science and Engineering, Sarala Birla University, Ranchi, Birla Knowledge City, Mahilong, Purulia Road, Jharkhand, India

2. Department of Computer Science and Engineering, Sarala Birla University, Ranchi, Birla Knowledge City, Mahilong, Purulia Road, Jharkhand, India

3. Department of Computer Science and IT, Arka Jain University, Jamshedpur, Jharkhand, India

Abstract

Data visualization is mandatory for different applications, such data interpretation, exploratory analysis, pattern identification, etc. It is rapidly used in the domain of Artificial Intelligence & Machine Learning (AI/ML), healthcare and medical analytics, cybersecurity, finance, IoT, etc. Although it is effectively used in several areas, but it has some issues such as large volume of data, choosing the right visualization technique, data quality, user interpretation, etc. In this paper, five visualization methods are used to illustrate a compact multi-view visualization in the form of an analytical. Finally, the results show that each chart illustrates a specific insight. Among all visualizations, scatter visualization provides richer information with the context of feature relationship and class separability.

Keywords

Data Visualization, Visual Analytics, Exploratory Data Analysis, Feature Relationships, Class Separability.