Advances in Data Analysis and Classification (ADAC)

Advances in Data Analysis and Classification (ADAC) is a peer-reviewed international scientific journal published by Springer Nature since 2007, serving as a leading forum for research at the intersection of statistics, data science, and computational methods. The journal focuses on methodological advances in the analysis of complex data structures, classification, clustering, pattern recognition, knowledge extraction, and statistical modelling. It encourages papers that introduce novel theoretical developments, validate rigorous statistical approaches, and illustrate practical applications across fields such as machine learning, artificial intelligence, bioinformatics, social sciences, economics, and engineering. A key emphasis of ADAC is on the integration of theory and practice, where methods not only advance the statistical foundations of data analysis but also demonstrate effectiveness with real-world datasets. Survey and review articles summarising emerging topics are also welcomed, helping researchers keep abreast of evolving trends in analytical techniques. The journal is supported by several international statistical and classification societies, reflecting its collaborative endorsement within the global scientific community. Indexed in major databases (e.g., Scopus, Science Citation Index Expanded), ADAC maintains a strong academic profile and contributes significantly to developments in data-driven analysis and classification methodologies.

Advances in Data Analysis and Classification (ADAC) is :-

• International, Peer-Reviewed, Open Access, Refereed, Applied Mathematics, Computer Science Applications, tructural, quantitative, or statistical approaches for the analysis of data, advances in classification, clustering, pattern recognition methods, strategies for modeling complex data and mining large data sets, methods for the extraction of knowledge from data , Online or Print , Quarterly Journal

• UGC Approved, ISSN Approved: P-ISSN P-ISSN: 1862-5347, E-ISSN: 1862-5355, Established: 2007, Impact Factor: 1.3
• Does Not Provide Crossref DOI

• Not indexed in Scopus, WoS, DOAJ, PubMed, UGC CARE