APPOINTMENT RULER EXCLUSIVE OF MULTIPLE TECHNO DECISION TREES REFLECTION TOWARDS RECITAL FOR EMPLOYABILITY
DOI:
https://doi.org/10.29121/ijetmr.v5.i3.2018.199Keywords:
Accurate Analyzation, Career Evaluation, Decision Trees, Techno FactorAbstract
Invention and new thoughts are discovered mainly from the student’s doubts and questions, for the most part of the word towards “why”. If questioning plays vital roles, in the same way, the sense of answering attitude incorrect approach is a big challenge for tutor and parents. At the same point in time, if this happens at the interviewing spot, the exact answer is required to fulfill the interviewer to accomplish the employability. Even though the ability of techno parameters are statistically shown as good, average or excellent. Accurate Performance of analyzation is enforced to fulfill and provide good decision over their employability through the academic event to make assured with the towering career growth. Decisions can be ruled up to access the resultant factor at any cause of situation to prolong the features with a high impact factor of “Presence of Mind” with the different attitude as Think different Methodologies
Downloads
References
Osmanbegović E, Suljić M. Data mining approach for predicting student performance. Economic Review. 2012 May; 10(1):3–12
Kabakchieva D. Predicting student performance by using data mining methods for classification. Cybernetics and information technologies. 2013 Mar; 13(1):61–72. DOI: https://doi.org/10.2478/cait-2013-0006
Ramesh VA, Parkavi P, Ramar K. Predicting student performance: a statistical and data mining approach. International journal of computer applications. 2013 Jan; 63:35–9. DOI: https://doi.org/10.5120/10489-5242
Harvey L. Defining and measuring employability. Quality in higher education. 2001 Jul; 7(2):97– 109 DOI: https://doi.org/10.1080/13538320120059990
Gokuladas VK. Technical and nontechnical education and the employability of engineering graduates: an Indian case study. International Journal of Training and Development. 2010 Jun; 14(2):130–43. DOI: https://doi.org/10.1111/j.1468-2419.2010.00346.x
Nghe NT, Janecek P, Haddawy P. A comparative analysis of techniques for predicting academic performance. 37th Annual Frontiers in Education Conference-Global Engineering: Knowledge without Borders, Opportunities without Passports 2007 Oct, T2G-7, 2007.
Oladokun VO, Adebanjo AT, Charles-Owaba OE. Predicting students’ academic performance using artificial neural network: A case study of an engineering course. The Pacific Journal of Science and Technology. 2008 May; 9(1):72–9.
Ramaswami M, Bhaskaran R. A study on feature selection techniques in educational data mining. ArXiv preprint arXiv. 2009 Dec; 1(1):7–11.
Kovacic Z. Early prediction of student success: Mining students’ enrolment data. 2010; 647–65.
Guruler H, Istanbullu A, Karahasan M. A new student performance analysing system using knowledge discovery in higher educational databases. Computers & Education. 2010 Aug; 55(1):247–54. DOI: https://doi.org/10.1016/j.compedu.2010.01.010
Affendey LS, Paris IH, Mustapha N, Suleiman MN, Muda Z. Ranking of influencing factors in predicting students’ academic performance. Information Technology Journal. 2010; 9(4):832–7. DOI: https://doi.org/10.3923/itj.2010.832.837
Baradwaj BK, Pal S. Mining educational data to analyze students’ performance. ArXiv preprint arXiv: 1201.3417. 2012 Jan; 2(6):63–9.
Huang S. Predictive modeling and analysis of student academic performance in an engineering dynamics course. 2011; 1–136.
Cheewaprakobkit P. Study of Factors Analysis Affecting Academic Achievement of Undergraduate Students in International Program. Proceedings of the International Multi Conference of Engineers and Computer Scientists. 2013; 1:13–5..
Mishra T, Kumar D, Gupta S. Mining Students’ Data for Prediction Performance. Fourth International Conference on Advanced Computing & Communication Technologies. 2014 Feb; 255–62. DOI: https://doi.org/10.1109/ACCT.2014.105
Romero C, Ventura S. Educational data mining: a review of the state of the art. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews). 2010 Nov; 40(6):601–18. DOI: https://doi.org/10.1109/TSMCC.2010.2053532
S.Radhimeenakshi,k.Latha,”Similarity Measures selection for Clustering stock Market time series Databases”, International Journal of Engineering Science,13878,2017
Downloads
Published
How to Cite
Issue
Section
License
License and Copyright Agreement
In submitting the manuscript to the journal, the authors certify that:
- They are authorized by their co-authors to enter into these arrangements.
- The work described has not been formally published before, except in the form of an abstract or as part of a published lecture, review, thesis, or overlay journal.
- That it is not under consideration for publication elsewhere.
- That its release has been approved by all the author(s) and by the responsible authorities – tacitly or explicitly – of the institutes where the work has been carried out.
- They secure the right to reproduce any material that has already been published or copyrighted elsewhere.
- They agree to the following license and copyright agreement.
Copyright
Authors who publish with International Journal of Engineering Technologies and Management Research agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors can enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or edit it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) before and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
For More info, please visit CopyRight Section