ADVERTISEMENT

Home|Journals|Articles by Year|Audio Abstracts
 

Research Article

EEO. 2021; 20(4): 3933-3941


Breast Cancer Prognosis And Detection: A Comparative Study Of Supervised Machine Learning Approaches

Neelam Singh, Vijay Laxmi Thapliyal, Vandana Rawat, Umang Garg.




Abstract

Cancer is one of the most dreadful disease taking heavy toll of human life in spite of advances in the field of medical science. Among all type of cancer, Breast Cancer is amongst the most usual category affecting women everywhere in the world and it is amid the foremost reason of death toll in women. A careful selection of techniques are required to analyse data and generate accurate results. Efficient techniques and methods are required to analyse data for accurate decision making and prediction. Machine Learning algorithms has achieved a bench mark when examination of data set is concerned for predictive analytics. Researchers and scientific community are working to achieve higher accuracy rate to predict ailments like breast cancer. Every technique and algorithm provide varying accuracy for different data sets and tools. In this study we will do a comparative investigation of different algorithms to find the highly appropriate and accurate breast cancer prediction algorithm. Algorithms like KNN, Decision Tree, SVM, Random forest are being used for the study.

Key words: Machine Learning, Predictive Analytics, KNN, Decision Tree, SVM, Random Forest.





publications
0
supporting
0
mentioning
0
contrasting
0
Smart Citations
0
0
0
0
Citing PublicationsSupportingMentioningContrasting
View Citations

See how this article has been cited at scite.ai

scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.



Bibliomed Article Statistics

7
6
5
11
14
9
7
18
14
19
16
12
R
E
A
D
S

7

9

6

9

10

7

7

10

20

10

6

11
D
O
W
N
L
O
A
D
S
050607080910111201020304
20242025

Full-text options


Share this Article


Online Article Submission
• ejmanager.com




ejPort - eJManager.com
Author Tools
About BiblioMed
License Information
Terms & Conditions
Privacy Policy
Contact Us

The articles in Bibliomed are open access articles licensed under Creative Commons Attribution 4.0 International License (CC BY), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.


We use cookies and other tracking technologies to work properly, to analyze our website traffic, and to understand where our visitors are coming from. More Info Got It!