• Vengala Rakshitha
• Dr. R. Jegadeesan
• P.Balakishan
• K.Jayasri
• B.Anjali

Grouping of information with high measurement and variable densities represents a surprising test to the customary thickness based bunching strategies. As of late, entropy, a numerical proportion of the vulnerability of data, can be utilized to quantify the outskirt level of tests in information space and furthermore select huge highlights in list of capabilities. It was utilized in our new system dependent on the sparsity-density entropy (SDE) to bunch the information with high measurement and variable densities. To begin with, SDE directs great testing for multidimensional information and chooses the agent highlights utilizing sparsity score entropy (SSE). Second, the grouping results and commotions are acquired embracing another thickness variable bunching technique called density entropy (DE). The adequacy and effectiveness of the proposed SDE structure are approved on engineered and genuine informational indexes in correlation with a few grouping calculations. The outcomes demonstrated that the proposed SDE structure simultaneously identified the clamors and handled the information with high measurement and different densities.

Density Entropy, Sparsity-Density Entropy, Sparsity Score Entropy

"DATA CLUSTERING FRAMEWORK BASED ON DENSITY", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.140-145, March-2019, Available :http://www.jetir.org/papers/JETIRAU06022.pdf

"DATA CLUSTERING FRAMEWORK BASED ON DENSITY", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp140-145, March-2019, Available at : http://www.jetir.org/papers/JETIRAU06022.pdf