2nd International Conference on Fostering Interdisciplinary Research In Health Sciences (ICFIRHS) 2019 (01-May-2019)        |

Journal :   Research Journal of Pharmacy and Technology

Volume No. :   12

Issue No. :  6

Year :  2019

Pages :   3059-3062

ISSN Print :  0974-3618

ISSN Online :  0974-360X


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A Survey on Machine Learning Algorithms and finding the best out there for the considered seven Medical Data Sets Scenario



Address:   R. M. Balajee*, K. Venkatesh
Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology, Avadi, Chennai.
*Corresponding Author
DOI No: 10.5958/0974-360X.2019.00518.3

ABSTRACT:
Today, researchers are focusing on many machine learning algorithms in general over the data’s available. Each and every algorithm will have certain characteristics and we need to test it on specific data set to say about its efficiency in particular. Each and every Algorithm efficiency will get varies according to the data set’s nature. Research based on medical science will be much useful to society in critical situations, so we are taking seven medical data sets scenario for our research work. A detailed survey over variety of machine learning algorithms like SVM, Naïve Bayes, Dession Tree, Random Forecast, K-Means Clustering, Partition Algorithm, Bayesian Algorithm, Hierarchical Algorithm, Missing Values, Low Variance, Principal Component Analysis, Rough Set Theory, etc, over the seven medical data sets scenario which is taken to study and the results will be made on the aspect, which algorithms are good for what kind of medical records.
KEYWORDS:
Machine Learning Algorithms, SVM, Naïve Bayes, Dession Tree, Random Forecast, K-Means Clustering, Partition Algorithm, Bayesian Algorithm, Hierarchical Algorithm, Missing Values, Low Variance, Principal Component Analysis, Rough Set Theory, Seven Medical Data Sets Scenario.
Cite:
R. M. Balajee, K. Venkatesh. A Survey on Machine Learning Algorithms and finding the best out there for the considered seven Medical Data Sets Scenario. Research J. Pharm. and Tech. 2019; 12(6):3059-3062.
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