Comparison of Logistic Regression and Support Vector Machine in Predicting Stroke Risk
Abstract
Keywords
Full Text:
PDFReferences
Bappenas. Tujuan Pembangunan Berkelanjutan [Internet]. 2022. Available from: https://sdgs.bappenas.go.id/tujuan-3/
WHO. World Stroke Day. 2021. Available from: https://www.who.int/southeastasia/news/detail/28-10-2021-world-stroke-day
Feigin VL, Brainin M, Norrving B, Martins S, Sacco RL, Hacke W, et al. World Stroke Organization (WSO): global stroke fact sheet 2022. International Journal of Stroke. 2022;17(1):18–29.
Rismawati Y, Tirta IM, Dewi YS. Klasifikasi Data Diagnosis Covid-19 Menggunakan Metode Support Vector Machine (Svm) Dan Generalized Linear Model (Glm). UNEJ e-Proceeding. 2022;246–52.
Tripathy A, Agrawal A, Rath SK. Classification of Sentimental Reviews Using Machine Learning Techniques. Procedia Computer Science. 2015;57:821–9.
Dangeti P. Statistics for machine learning. Packt Publishing Ltd; 2017.
Suthaharan S. Support Vector Machine-Machine Learning Models and Algorithms for Big Data Classification. Integrated Series in Information Systems. 2016;36.
Schölkopf B, Smola A. Support vector machines and kernel algorithms. In: Encyclopedia of Biostatistics. Wiley; 2005. p. 5328–35.
Kernel methods. In: Data Mining Algorithms [Internet]. Chichester, UK: John Wiley & Sons, Ltd; 2015 [cited 2023 Feb 13]. p. 454–97. Available from: https://onlinelibrary.wiley.com/doi/10.1002/9781118950951.ch16
Hosmer DW, Lemeshow S, Sturdivant RX. Applied logistic regression. Third edition. Hoboken, New Jersey: Wiley; 2013. 1 p. (Wiley series in probability and statistics).
Stoltzfus JC. Logistic Regression: A Brief Primer: LOGISTIC REGRESSION: A BRIEF PRIMER. Academic Emergency Medicine. 2011 Oct;18(10):1099–104.
Hilbe JM. Practical guide to logistic regression. crc Press; 2016.
James G, Witten D, Hastie T, Tibshirani R. An introduction to statistical learning. Vol. 112. Springer; 2013.
Joundi RA, Patten SB, Williams JV, Smith EE. Vascular risk factors and stroke risk across the life span: A population-representative study of half a million people. International Journal of Stroke. 2022;17474930211070682.
Piegorsch WW. Confusion Matrix. Wiley StatsRef: Statistics Reference Online. 2014;1–4.
Al Azies H, Trishnanti D, Mustikawati P.H E. Comparison of Kernel Support Vector Machine (SVM) in Classification of Human Development Index (HDI). IJPS. 2019 Dec 30;0(6):53.
Yekkehkhany B, Safari A, Homayouni S, Hasanlou M. A Comparison Study Of Different Kernel Functions For Svm-Based Classification Of Multi-Temporal Polarimetry Sar Data. Int Arch Photogramm Remote Sens Spatial Inf Sci. 2014 Oct 22;XL-2/W3:281–5.
DOI: http://dx.doi.org/10.12962/j27213862.v7i2.20420
Refbacks
- There are currently no refbacks.
Inferensi by Department of Statistics ITS is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Based on a work at https://iptek.its.ac.id/index.php/inferensi.
ISSN: 0216-308X
e-ISSN: 2721-3862
View My Stats