Visual approaches for exploratory data analysis: The VAT family of algorithms
If you are a first time user and want to acquaint yourself with the VAT family of algorithms and want to apply them to your data, install the VEDA (Visual Exploratory Data Analysis) MATLAB toolkit, which is user friendly implementation of various members of the visual assessment of clustering tendency (VAT) family of algorithms for exploratory data analysis.
Please cite the following paper if you find this useful:
D. Kumar and J. C. Bezdek, "Visual Approaches for Exploratory Data Analysis: A Survey of the Visual Assessment of Clustering Tendency (VAT) Family of Algorithms," in IEEE Systems, Man, and Cybernetics Magazine, vol. 6, no. 2, pp. 10-48, April 2020, doi: 10.1109/MSMC.2019.2961163.
To experiment futher, go to "VAT-iVAT" for small data, "clusiVAT" for large volume data having large number of datapoints, and "inc-VAT_inc-iVAT_dec-VAT_dec-iVAT" for streaming data.
Please send all your queries and feedback to Dheeraj Kumar at genuine.dheeraj@gmail.com