The purpose of this research is to evaluate the performance of four distinct approaches to prediction—namely, Logistic Regression (LR), Decision Tree (DT), K Means Algorithm (KMA), and Support Vector Machine (SVM) Classification—in order to determine which one yields the most accurate results. The Following are the Components and Methods: When testing the Classification technique, a dataset consisting of 778 items is employed. In the subject of education, the Logistic Regression (LR), K-Means, Decision Tree, and Support Vector Machine (SVM) are all viable frameworks that have been suggested and developed for the College Recommendation system. K-Means was the first of these frameworks to be built. Through the use of G power, we were able to establish that we need 55 people for each of the conditions. Both the precision and accuracy of the classifiers have been analysed and recognised. Through the use of G Power, we were able to establish that each of our groups required 55 individuals. The College dataset had a sample size of 303 students, 76 attributes, and a few blanks in addition to those numbers. A clinical study was conducted to establish the appropriate size of the sample, and the following were the findings: 80 percent predictive power on the pretest, 0.05 alpha, and a 1. When applied to the College Recommendation System data set, the results demonstrate that the K-Means classifier produces the same group that it predicts (50 percent). This is also the case for Logistic regression (86 percent), Decision Tree (88 percent), K-Means (50 percent), and Support Vector Machine (50 percent) (85 percent). The value assigned to significance is zero. Consequently, DT performs better than LR, SVM, and K-Means. The findings indicate that Decision Tree offers greater performance in terms of precision and accuracy when compared to SVM, LR, DT, and K-Means. This is shown by the fact that Decision Tree.

1.
F.
Liu
, “
Personalized Recommendation System of Resource Database for College Students’ Innovation and Entrepreneurship
,”
2021 13th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA
).
2021
. doi: .
2.
Y.-K.
Ng
and
J.
Linn
, “
CrsRecs: A personalized course recommendation system for college students
,”
2017 8th International Conference on Information, Intelligence, Systems & Applications (IISA
).
2017
. doi: .
3.
N.
Karbhari
,
A.
Deshmukh
, and
V. D.
Shinde
, “
Recommendation system using content filtering: A case study for college campus placement
,”
2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS
).
2017
. doi: .
4.
K.-S.
Shin
,
T. S.
Lee
, and
H.-J.
Kim
, “
An application of support vector machines in bankruptcy prediction model
,”
Expert Systems with Applications
, vol.
28
, no.
1
. pp.
127
135
,
2005
. doi: .
5.
V.
Sharma
,
T.
Trehan
,
R.
Chanana
, and
S.
Dawn
, “
StudieMe: College Recommendation System
,”
2019 3rd International Conference on Recent Developments in Control, Automation & Power Engineering (RDCAPE
).
2019
. doi: .
6.
S. V.
Hovale
,
R V College of Engineering, Visvesvaraya technological university, Bangalore, and G. Poonam
, “
Survey Paper on Recommendation System using Data Mining Techniques
,”
International Journal Of Engineering And Computer Science
.
2016
. doi: .
7.
D.
Zhu
,
Z.-H.
Wu
,
L.
Xu
, and
D.-L.
Yang
, “
Single sample scoring of hepatocellular carcinoma: A study based on data mining
,”
Int. J. Immunopathol. Pharmacol
., vol.
35
, p.
20587384211018389
, Jan.
2021
.
8.
T. T.
Watt
,
K.
Hartfield
,
S.
Kim
, and
N.
Ceballos
, “
Adverse childhood experiences contribute to race/ethnic differences in post-secondary academic performance among college students
,”
J Am. Coll. Health
, pp.
1
9
, Jul.
2021
.
9.
Ananthaswamy
,
V.
,
Renganathan
,
K.
,
Analytical solutions of the concentration of sugar and glucose for enzymatic hydrolysis process
.
Materials Today: Proceedings
,
37
, pp.
298
302
.
10.
S.
Perumal
,
S.
Rajendrian
,
V.
Venkatraman
,
D.
Sundaresan
&
L.
Pandiyan
L. (
2020
).
Experimental study about thermal resistance of windows with air gap between two glasses used in single houses
.
Thermal Science
,
24
(
1 Part B
),
515
518
.
11.
I.
Saraswathi
,
J.
Saikarthik
,
K. Senthil
Kumar
,
K.
MadhanSrinivasan
,
M.
Ardhanaari
, and
R.
Gunapriya
, “
Impact of COVID-19 outbreak on the mental health status of undergraduate medical students in a COVID-19 treating medical college: a prospective longitudinal study
,”
PeerJ
, vol.
8
, p.
e10164
, Oct.
2020
.
12.
A. S. S.
Girija
,
E. M.
Shankar
, and
M.
Larsson
, “
Could SARS-CoV-2-Induced Hyperinflammation Magnify the Severity of Coronavirus Disease (CoViD-19) Leading to Acute Respiratory Distress Syndrome?
,”
Frontiers in immunology
, vol.
11
. p.
1206
, May 27,
2020
.
13.
S.
Chozhavendhan
,
M. Vijay Pradhap
Singh
,
B.
Fransila
,
R. Praveen
Kumar
, and
G. Karthiga
Devi
, “
A review on influencing parameters of biodiesel production and purification processes
,”
Current Research in Green and Sustainable Chemistry
, vol.
1–2
, pp.
1
6
, Feb.
2020
.
14.
A.
Mohan
,
S.
Karthika
,
J.
Ajith
,
L.
Dhal
, and
M.
Tholkapiyan
, “
Investigation on ultra high strength slurry infiltrated multiscalefibre reinforced concrete
,”
Materials Today: Proceedings
, vol.
22
, pp.
904
911
, Jan.
2020
.
15.
A. R. Pradeep
Kumar
et al, “
Diagnosis of Vertical Root Fractures by Cone-beam Computed Tomography in Root-filled Teeth with Confirmation by Direct Visualization: A Systematic Review and Meta-Analysis
,”
J. Endod
., vol.
47
, no.
8
, pp.
1198
1214
, Aug.
2021
.
16.
S.
Dinesh
et al, “
Influence of wood dust fillers on the mechanical, thermal, water absorption and biodegradation characteristics of jute fiber epoxy composites
,”
J. Polym. Res
., vol.
27
, no.
1
, p.
9
, Dec.
2019
.
17.
S.
Babu
and
S.
Jayaraman
, “
An update on β-sitosterol: A potential herbal nutraceutical for diabetic management
,”
Biomed. Pharmacother
., vol.
131
, p.
110702
, Nov.
2020
.
18.
V.
Shanmugam
et al, “
Fatigue behaviour of FDM-3D printed polymers, polymeric composites and architected cellular materials
,”
Int. J. Fatigue
, vol.
143
, no.
106007
, p.
106007
, Feb.
2021
.
19.
D.
Chandramohan
,
SD
Kumar
and
Sudhakar
M
, ‘
Mechanical and thermal properties of Jute/alovera hybrid natural fiber reinforced composites
’,
AIP Conference Proceedings
2283
(
1
),
020084
, Oct
2020
.
20.
Dinesh Kumar
Singaravelu
, ‘
Diesel Engine Performance on Chlorella vulgaris Biodiesel
’,
Journal of Scientific and Industrial Research, NISCAIR Publisher
, Vol.
79
, Issue
9
, Sep
2020
, pp.
843
845
, 2020.
21.
Dinesh Kumar
Singaravelu
, ‘
Diesel Engine Emission Characteristics Study using Algae Biofuel
’,
Journal of Scientific and Industrial Research, NISCAIR Publisher
, Vol.
79
, Issue
6
, June
2020
, pp.
547
551
, 2020.
22.
K.
Muthukumar
,
R.
Saravanan
and
V.
Dhinakaran
, ‘
Investigation on waste tyre oil with diesel for detection of density, Kinematic and dynamic viscosities evaluation of various combinations in volume basis
’,
AIP Conference Proceedings
2283
(
1
),
020123
, Oct
2020
.
23.
T.
Sathish
, ‘
Optimization of chlorella vulgaris Biodiesel usage in Diesel Engine
’,
Journal of Scientific and Industrial Research, NISCAIR Publisher
, Vol.
79
, Issue
8
, Aug
2020
, pp.
750
752
, 2020.
24.
M.
Mehta
et al, “
Cellular signalling pathways mediating the pathogenesis of chronic inflammatory respiratory diseases: an update
,”
Inflammopharmacology
, vol.
28
, no.
4
, pp.
795
817
, Aug.
2020
.
25.
M.
Vairavel
,
E.
Devaraj
, and
R.
Shanmugam
, “
An eco-friendly synthesis of Enterococcus sp.-mediated gold nanoparticle induces cytotoxicity in human colorectal cancer cells
,”
Environ. Sci. Pollut. Res. Int
., vol.
27
, no.
8
, pp.
8166
8175
, Mar.
2020
.
26.
C. N.
Marsh
and
S. Allen
Wilcoxon
, “
Underutilization of Mental Health Services Among College Students: An Examination of System-Related Barriers
,”
Journal of College Student Psychotherapy
, vol.
29
, no.
3
. pp.
227
243
,
2015
. doi: .
27.
Babu
,
A.B.
,
2012
.
Design and development of artificial neural network based tamil unicode symbols identification system
.
International Journal of Computer Science Issues (IJCSI)
,
9
(
1
), p.
388
.
28.
S.
Vashishta
et al, “
ASSESSMENT OF ATTITUDE OF MARRIED MALES REGARDING VASECTOMY IN RURAL AND URBAN AREAS OF CHANDIGARH
,”
International Journal of Advanced Research
, vol.
8
, no.
02
. pp.
1044
1047
,
2020
. doi: .
29.
An Enhanced Text Mining Technique using Big Data for Students Attendance Management System
,”
International Journal of Modern Trends in Engineering & Research
, vol.
4
, no.
7
. pp.
236
243
,
2017
. doi: .
30.
Y.
Zhao
,
M.
Yin
,
C.
Zhu
,
C.
Tan
,
S.
Hu
, and
D.
Liu
, “
Can situations awaken emotions? The compilation and evaluation of the Emotional Situation Sentence System (ESSS
),”
PLoS One
, vol.
16
, no.
7
, p.
e0252671
, Jul.
2021
.
31.
L. I.
Hitchcock
et al, “
Why We Want Our Students to Learn about Poverty and Healthcare: Sharing Our Students’ Experiences from Poverty Simulations
,”
Health Commun
., pp.
1
5
, Jul.
2021
.
This content is only available via PDF.
You do not currently have access to this content.