A novel approach to predict competency and the hidden risk factor by using various machine learning classifiers

被引:0
|
作者
Stalin, M. [1 ,2 ]
Kalyani, S. [1 ]
机构
[1] Kamaraj Coll Engn & Technol, Elect & Elect Engn, Virudunagar, India
[2] Kamaraj Coll Engn & Technol, Elect & Elect Engn, Virudunagar, Tamilnadu, India
关键词
Decision tree; random forest; support vector; logistic regression classifier;
D O I
10.1080/00051144.2023.2200347
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In a survey conducted in the year 2020, we came to know that India's around 50% of population includes young people of the age group of 25 and students. Guiding this young mass in the right way and strengthening their future is a huge responsibility put over the head of the elder citizens of India such as their parents teachers and professors. This paper aims to build a model that can predict the students' competency level and the risk factors or the fields where he needs to put their effort to improve themselves, and this model also helps the parents, professors and Educational institutes to know about their children's and students in which zone they stand, are they ready to compete with others. This analysis is done by using different ML bifurcation algorithms. Also we aim to find the best classifier which can emerge with the highest predicting accuracy among all other classifiers to the above-said problem. The accuracy of 88.5% is achieved through the proposed machine learning algorithm for particular education datasets which have been taken into consideration.
引用
收藏
页码:550 / 564
页数:15
相关论文
共 50 条
  • [21] A novel approach to fake news detection in social networks using genetic algorithm applying machine learning classifiers
    Choudhury, Deepjyoti
    Acharjee, Tapodhir
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2023, 82 (06) : 9029 - 9045
  • [22] BCBSLA APPROACH USING NATURAL LANGUAGE PROCESSING (NLP) AND MACHINE LEARNING TO PREDICT THE RISK OF HOSPITALIZATIONS
    Holloway, J.
    Neely, C.
    Yuan, X.
    Zhang, Y.
    Ouyang, J.
    Cantrell, D.
    Chaisson, J.
    Tisdale, K.
    Bergeron, T.
    Nigam, S.
    [J]. VALUE IN HEALTH, 2019, 22 : S266 - S266
  • [23] Comparative Study of Various Machine Learning Classifiers on Medical Data
    Karankar, Nilima
    Shukla, Pragya
    Agrawal, Niyati
    [J]. 2017 7TH INTERNATIONAL CONFERENCE ON COMMUNICATION SYSTEMS AND NETWORK TECHNOLOGIES (CSNT), 2017, : 267 - 271
  • [24] Heart Disease Risk Prediction Using Machine Learning Classifiers with Attribute Evaluators
    Reddy, Karna Vishnu Vardhana
    Elamvazuthi, Irraivan
    Abd Aziz, Azrina
    Paramasivam, Sivajothi
    Chua, Hui Na
    Pranavanand, S.
    [J]. APPLIED SCIENCES-BASEL, 2021, 11 (18):
  • [25] A Machine Learning Approach to ADHD Diagnosis Using Mutual Information and Stacked Classifiers
    Chauhan, Nishant
    Choi, Byung-Jae
    [J]. INTERNATIONAL JOURNAL OF FUZZY LOGIC AND INTELLIGENT SYSTEMS, 2024, 24 (01) : 10 - 18
  • [26] Using machine learning to predict risk of opioid overdose in Medicare
    Lo-Ciganic, Weihsuan Jenny
    Huang, James L.
    Zhang, Hao H.
    Weiss, Jeremy C.
    Wu, Yonghui
    Kwoh, Chian K.
    Donohue, Julie M.
    Cochran, Jerry
    Gordon, Adam J.
    Malone, Daniel C.
    Kuza, Courtney C.
    Gellad, Walid F.
    [J]. PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, 2019, 28 : 230 - 230
  • [27] Can machine learning predict cardiac risk using mammography?
    Lip, Gerald
    O'Regan, Declan P.
    [J]. EUROPEAN HEART JOURNAL-CARDIOVASCULAR IMAGING, 2024, 25 (04) : 467 - 468
  • [28] A novel machine-learning based approach to predict flares of psoriasis
    Ramelyte, E.
    Djamei, V.
    Maul, T. J.
    Anzengruber, F.
    Navarini, A.
    [J]. EXPERIMENTAL DERMATOLOGY, 2018, 27 (03) : E44 - E45
  • [29] Casting Online Votes: To Predict Offline Results Using Sentiment Analysis by machine learning Classifiers
    Juneja, Pragya
    Ojha, Uma
    [J]. 2017 8TH INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION AND NETWORKING TECHNOLOGIES (ICCCNT), 2017,
  • [30] Machine Learning Classifiers using Stochastic Logic
    Liu, Yin
    Venkataraman, Hariharasudhan
    Zhang, Zisheng
    Parhi, Keshab K.
    [J]. PROCEEDINGS OF THE 34TH IEEE INTERNATIONAL CONFERENCE ON COMPUTER DESIGN (ICCD), 2016, : 408 - 411