DESIGN OF SPORTS SELECTION ARCHITECTURE USING RECURSIVE NEURAL NETWORK AND K-MEANS CLUSTERING ALGORITHM

DESIGN OF SPORTS SELECTION ARCHITECTURE USING RECURSIVE NEURAL NETWORK AND K-MEANS CLUSTERING ALGORITHM
Author(s):
K. Vaishnavi, Dr. Mahalakshmi
Keywords:
FitRec dataset, Jsion, Pyspark, RNN, EDA
Abstract
Sports are essential part for healthy life for all human being, as it keeps the person fit and agility. Sports also helps person for healthy mind. Practice is very essential for the person in sports. If human body or health is not suitable for the particular sport, then the person cannot lead the sport cycle to the successful part. Selecting the sport is very essential for the success. This paper proposed the system for selecting the correct person to the sports which the person is matched in the boundary of practice and healthy life according to the several perceptions of calculation based speed, weight, height and heart rate. This implementation is developed using MatLab software. This system was implemented with FitRec dataset with the base of Jsion file read with pyspark. For the selection process, this system was designed by Recursive Neural Network (RNN) and for grouping the collected data is completed by K-means clustering algorithm. Result is produced Exploratory Data Analysis (EDA). This system provides the 89% of accuracy rate among the sample size N chosen by the user.
Article Details
Unique Paper ID: 153904 Publication Volume & Issue: Volume 8, Issue 9 Page(s): 194 - 198
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