Fr. 65.00

Analyzing Student Performance Prediction: Meta Stacking Classification

English · Paperback / Softback

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Description

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This book is a conglomerate framework to investigate, analyze and interpret academic attributes influencing students' performance pursuing Technical education. The vital goal of this research is selection of most optimal features influencing the Cumulative GPA as analogy of academic excellence. Various statistical tools and classifiers are of extracurricular activities on university management performance, in order to bring real contribution in terms of increased quality of university management by diversifying the extracurricular activities' offer within universities, with the effect on performance management growth. The research includes a detailed radiography of specialized studies from the field, in order to determine the current state of scientific knowledge in conceptual terms, and highlights the functionality of the university system. Quantitatively, Meta Stacked Regression model is compared with traditional linear regression and neural networks for feature importance in metrics of mean square error.

About the author










Smita Pallavi has done B.E.(CSE), MBA(IT) and PhD (IT) at Birla Institute of Technology, Mesra-Patna Campus, India. With teaching experience of 13 years, she has handled major consultancy projects under Government of Bihar. Her publications include SCI, Scopus and International journals in Soft Computing, Data Mining and Optimization Algorithms.

Product details

Authors Smita Pallavi
Publisher LAP Lambert Academic Publishing
 
Languages English
Product format Paperback / Softback
Released 04.06.2018
 
EAN 9786139828364
ISBN 9786139828364
No. of pages 104
Subject Social sciences, law, business > Sociology > Methods of empirical and qualitative social research

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