Cluster and logistic regression distribution of students’ performance by classification

Nareena Soomro; Fahad Razaque; Safeeullah Soomro; Shoaib Shaikh; Natesh Kumar; Ghulam e.Mustafa Abro; Ghulam Abid

doi:10.1007/978-3-319-95450-9_18

Cluster and logistic regression distribution of students’ performance by classification

Nareena Soomro^*
, Fahad Razaque
, Safeeullah Soomro
, Shoaib Shaikh
, Natesh Kumar
, Ghulam e.Mustafa Abro
, Ghulam Abid

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In the research cluster based logistic regression model on student result, performance at computing department, and other demographics to predict whether or not student will annually enroll if admitted that help the campus administrators to manage registrations. In this study, deals with performance and analysis of examination results’ performance of students from computing department by also establishing general assessment. However, it cannot be stand-alone and only serves to compliment campus administrator of decision making procedure to manage registrations effectually. Predict students of educational performance are critical for scholastic departments because planned program can be scheduled in maintaining performance of students during their period of studies in departments. The demographic profile of students and fourth year of academic are used as predictor variable for performance of students educational in academic program.

Original language	English
Title of host publication	Emerging Technologies in Computing - First International Conference, iCETiC 2018, Proceedings
Editors	Mahdi H. Miraz, Peter Excell, Andrew Ware, Maaruf Ali, Safeeullah Soomro
Publisher	Springer Verlag
Pages	209-219
Number of pages	11
ISBN (Print)	9783319954493
DOIs	https://doi.org/10.1007/978-3-319-95450-9_18
State	Published - 2018
Externally published	Yes
Event	1st International Conference on Emerging Technologies in Computing, iCETiC 2018 - London, United Kingdom Duration: 23 Aug 2018 → 24 Aug 2018

Publication series

Name	Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume	200
ISSN (Print)	1867-8211

Conference

Conference	1st International Conference on Emerging Technologies in Computing, iCETiC 2018
Country/Territory	United Kingdom
City	London
Period	23/08/18 → 24/08/18

Bibliographical note

Publisher Copyright:
© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018.

Keywords

Cluster
Logistic regression
Performance
Probability

ASJC Scopus subject areas

Computer Networks and Communications

Access to Document

10.1007/978-3-319-95450-9_18

Cite this

Soomro, N., Razaque, F., Soomro, S., Shaikh, S., Kumar, N., Abro, G. E. M., & Abid, G. (2018). Cluster and logistic regression distribution of students’ performance by classification. In M. H. Miraz, P. Excell, A. Ware, M. Ali, & S. Soomro (Eds.), Emerging Technologies in Computing - First International Conference, iCETiC 2018, Proceedings (pp. 209-219). (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 200). Springer Verlag. https://doi.org/10.1007/978-3-319-95450-9_18

Soomro, Nareena ; Razaque, Fahad ; Soomro, Safeeullah et al. / Cluster and logistic regression distribution of students’ performance by classification. Emerging Technologies in Computing - First International Conference, iCETiC 2018, Proceedings. editor / Mahdi H. Miraz ; Peter Excell ; Andrew Ware ; Maaruf Ali ; Safeeullah Soomro. Springer Verlag, 2018. pp. 209-219 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST).

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abstract = "In the research cluster based logistic regression model on student result, performance at computing department, and other demographics to predict whether or not student will annually enroll if admitted that help the campus administrators to manage registrations. In this study, deals with performance and analysis of examination results{\textquoteright} performance of students from computing department by also establishing general assessment. However, it cannot be stand-alone and only serves to compliment campus administrator of decision making procedure to manage registrations effectually. Predict students of educational performance are critical for scholastic departments because planned program can be scheduled in maintaining performance of students during their period of studies in departments. The demographic profile of students and fourth year of academic are used as predictor variable for performance of students educational in academic program.",

keywords = "Cluster, Logistic regression, Performance, Probability",

author = "Nareena Soomro and Fahad Razaque and Safeeullah Soomro and Shoaib Shaikh and Natesh Kumar and Abro, \{Ghulam e.Mustafa\} and Ghulam Abid",

note = "Publisher Copyright: {\textcopyright} ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018.; 1st International Conference on Emerging Technologies in Computing, iCETiC 2018 ; Conference date: 23-08-2018 Through 24-08-2018",

year = "2018",

doi = "10.1007/978-3-319-95450-9\_18",

language = "English",

isbn = "9783319954493",

series = "Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST",

publisher = "Springer Verlag",

pages = "209--219",

editor = "Miraz, \{Mahdi H.\} and Peter Excell and Andrew Ware and Maaruf Ali and Safeeullah Soomro",

booktitle = "Emerging Technologies in Computing - First International Conference, iCETiC 2018, Proceedings",

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}

Soomro, N, Razaque, F, Soomro, S, Shaikh, S, Kumar, N, Abro, GEM & Abid, G 2018, Cluster and logistic regression distribution of students’ performance by classification. in MH Miraz, P Excell, A Ware, M Ali & S Soomro (eds), Emerging Technologies in Computing - First International Conference, iCETiC 2018, Proceedings. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, vol. 200, Springer Verlag, pp. 209-219, 1st International Conference on Emerging Technologies in Computing, iCETiC 2018, London, United Kingdom, 23/08/18. https://doi.org/10.1007/978-3-319-95450-9_18

Cluster and logistic regression distribution of students’ performance by classification. / Soomro, Nareena; Razaque, Fahad; Soomro, Safeeullah et al.
Emerging Technologies in Computing - First International Conference, iCETiC 2018, Proceedings. ed. / Mahdi H. Miraz; Peter Excell; Andrew Ware; Maaruf Ali; Safeeullah Soomro. Springer Verlag, 2018. p. 209-219 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 200).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Cluster and logistic regression distribution of students’ performance by classification

AU - Soomro, Nareena

AU - Razaque, Fahad

AU - Soomro, Safeeullah

AU - Shaikh, Shoaib

AU - Kumar, Natesh

AU - Abro, Ghulam e.Mustafa

AU - Abid, Ghulam

N1 - Publisher Copyright: © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018.

PY - 2018

Y1 - 2018

N2 - In the research cluster based logistic regression model on student result, performance at computing department, and other demographics to predict whether or not student will annually enroll if admitted that help the campus administrators to manage registrations. In this study, deals with performance and analysis of examination results’ performance of students from computing department by also establishing general assessment. However, it cannot be stand-alone and only serves to compliment campus administrator of decision making procedure to manage registrations effectually. Predict students of educational performance are critical for scholastic departments because planned program can be scheduled in maintaining performance of students during their period of studies in departments. The demographic profile of students and fourth year of academic are used as predictor variable for performance of students educational in academic program.

AB - In the research cluster based logistic regression model on student result, performance at computing department, and other demographics to predict whether or not student will annually enroll if admitted that help the campus administrators to manage registrations. In this study, deals with performance and analysis of examination results’ performance of students from computing department by also establishing general assessment. However, it cannot be stand-alone and only serves to compliment campus administrator of decision making procedure to manage registrations effectually. Predict students of educational performance are critical for scholastic departments because planned program can be scheduled in maintaining performance of students during their period of studies in departments. The demographic profile of students and fourth year of academic are used as predictor variable for performance of students educational in academic program.

KW - Cluster

KW - Logistic regression

KW - Performance

KW - Probability

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DO - 10.1007/978-3-319-95450-9_18

M3 - Conference contribution

AN - SCOPUS:85051107719

SN - 9783319954493

T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST

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EP - 219

BT - Emerging Technologies in Computing - First International Conference, iCETiC 2018, Proceedings

A2 - Miraz, Mahdi H.

A2 - Excell, Peter

A2 - Ware, Andrew

A2 - Ali, Maaruf

A2 - Soomro, Safeeullah

PB - Springer Verlag

T2 - 1st International Conference on Emerging Technologies in Computing, iCETiC 2018

Y2 - 23 August 2018 through 24 August 2018

ER -

Soomro N, Razaque F, Soomro S, Shaikh S, Kumar N, Abro GEM et al. Cluster and logistic regression distribution of students’ performance by classification. In Miraz MH, Excell P, Ware A, Ali M, Soomro S, editors, Emerging Technologies in Computing - First International Conference, iCETiC 2018, Proceedings. Springer Verlag. 2018. p. 209-219. (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST). doi: 10.1007/978-3-319-95450-9_18

Cluster and logistic regression distribution of students’ performance by classification

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this