Predicting Student’s Campus Placement Probability using Binary Logistic Regression
D. Satish Kumar1, P. Bindu2, Zailan Bin Siri3, D.S. Rao4, S. Anusha5
1D. Satish Kumar, Department of Mathematics, KoneruLakshmaiah Education Foundation, Vaddeswaram, India.
2P. Bindu, Zailan Bin Siri, Institute of Mathematical Sciences, Faculty of Science, University of Malaya, Kuala Lumpur, Malaysia.
4D.S. Rao, Business School, Koneru Lakshmaiah Education Foundation, Vaddeswaram, India
5S. Anusha, Department of Mathematics, Koneru Lakshmaiah Education Foundation, Vaddeswaram, India.
Manuscript received on November 20, 2019. | Revised Manuscript received on November 28, 2019. | Manuscript published on 30 November, 2019. | PP: 7605-7607 | Volume-8 Issue-4, November 2019. | Retrieval Number: D5347118419/2019©BEIESP | DOI: 10.35940/ijrte.D5347.118419
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Abstract: Understudies trying to precise instructions for the most part chose instructive establishment with a notable popularity inside the primary settings. Many of those establishments several instances reputation controlled through bundles of compensation presented with the aid of the complainant for his understudies. In this putting it’s far appropriate to explore and distinguish variables which could have an effect on the composition of the reason replacement special education .The threat within the State of Andhra Pradesh which has a excessive grouping established order of a unique training became appointed as research region. A careful survey of writing ends in a diagnosed proof of six determinants of speculative state of affairs inside the alternative special motive training.A arbitrary eg MBA alternative function information 250 is assembled from various organizations and located parallel relapse version became suited for the six signs for assessing information possibilities for placing alternative purpose. Assessed Results show that the possibility of putting in a simple exam is inspired by using 4 signs: CGPA, Specializes in PG, UG and Specialization in Gender.
Keywords: Campus Placements Technical Education Odds Ratio Binary Logistic Regression Goodness of Fit Confusion Matrix.
Scope of the Article: Smart Learning and Innovative Education Systems.