Zobrazeno 1 - 10
of 66
pro vyhledávání: '"S. Magesh Kumar"'
Autor:
R. Rameshwar, K. Meenakshi, Gowtham Hanumanram, R. Kannan, S. Magesh Kumar, J. Damodaran, S. Nandhini
Publikováno v:
Indian Heart Journal, Vol 74, Iss 2, Pp 144-147 (2022)
Externí odkaz:
https://doaj.org/article/e516846496e946ecade821f1cfdb6f11
Autor:
V., Srihari1, S., Magesh kumar2
Publikováno v:
Journal of Pharmaceutical Negative Results. 2022 Special Issue, Vol. 13, p1566-1572. 7p.
Autor:
S. Vijayalakshmi, S. Magesh Kumar
Publikováno v:
Intelligent Automation & Soft Computing. 36:2915-2931
Autor:
P. Shanmuga Prabha, S. Magesh Kumar
Publikováno v:
Intelligent Automation & Soft Computing. 36:3101-3119
Autor:
S. Ashwini, S. Magesh Kumar
Publikováno v:
Intelligent Automation & Soft Computing. 36:3043-3056
Autor:
Pathipati Yasasvi, S. Magesh Kumar
Publikováno v:
2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N).
Autor:
P. Varshitha Reddy, S. Magesh Kumar
Publikováno v:
2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N).
Publikováno v:
2022 5th International Conference on Contemporary Computing and Informatics (IC3I).
Autor:
V. Abhinaya, S. Magesh Kumar
Publikováno v:
Journal of Pharmaceutical Research International. :150-158
Background: Kidneys have a significant role in the metabolism, degradation and excretion of thyroid hormones. Both thyroid hormones and kidney functions have a multifaceted mutual interdependence. Objectives: To find out the possible association betw
Autor:
Pathipati Yasasvi, S. Magesh Kumar
Publikováno v:
Advances in Parallel Computing Algorithms, Tools and Paradigms ISBN: 9781643683140
The aim of this work is to conclude the credit card approval using XGBoost algorithm and compare it with Random Forest (RF) to improve accuracy. Prediction of credit card approval using XGboost Classifier with sample size of N=10 and logistic regress
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b5e4345337a4d437a253499221fda8b2
https://doi.org/10.3233/apc220083
https://doi.org/10.3233/apc220083