International Research journal of Management Science and Technology

  ISSN 2250 - 1959 (online) ISSN 2348 - 9367 (Print) New DOI : 10.32804/IRJMST

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ENHANCING SPONDYLOLISTHESIS DIAGNOSIS ACCURACY THROUGH DBSCAN: A HYBRID APPROACH WITH K-NN CLASSIFIER

    2 Author(s):  DR. DEEPIKA SARAVAGI,DR. MANISHA SARAVAGI

Vol -  15, Issue- 4 ,         Page(s) : 393 - 402  (2024 ) DOI : https://doi.org/10.32804/IRJMST

Abstract

The Density-Based Spatial Clustering of Applications with Noise - Based Attribute Weighting (DBSCANBAW) is a new data pre-processing technique that this study presents a way to diagnose spondylolisthesis.

[1]  Z. Yan et al., “DBSCAN-KNN-GA: a multi Density-Level Parameter-Free clustering algorithm,” In IOP Conference Series: Materials Science and Engineering, 2020, Vol. 715, no. 1, p. 012023.
[2]     T. Zhang, L. Zhong, and B. Yuan, “A Critical Note on the Evaluation of Clustering Algorithms,” arXiv preprint arXiv:1908.03782, 2019.

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