relation: https://khub.utp.edu.my/scholars/9866/
title: Liver Patient Classification using Logistic Regression
creator: Adil, S.H.
creator: Ebrahim, M.
creator: Raza, K.
creator: Azhar Ali, S.S.
creator: Ahmed Hashmani, M.
description: In this research paper, we have applied machine learning approach to classify liver patient (i.e., Liver Patient or Not Liver Patient) using patient gender and laboratory medical test data. The labelled dataset was published on UCI machine learning repository as "Indian Liver Patient Records". The motivation behind this work is to apply simple and less computational classification technique like Logistic Regression and compare its results with earlier results obtained on the same dataset by other researchers. The classification results of Logistic regression have proved its significance on this dataset by achieving better classification accuracy than NBC (Naïve Bayes Classifier), C4.5 (Decision Tree), SVM (Support Vector Machine), ANN (Artificial Neural Network), and KNN (K Nearest Neighbors) as presented in Ramana et al., research paper. © 2018 IEEE.
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2018
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Adil, S.H. and Ebrahim, M. and Raza, K. and Azhar Ali, S.S. and Ahmed Hashmani, M.  (2018) Liver Patient Classification using Logistic Regression.  In: UNSPECIFIED.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057078574&doi=10.1109%2fICCOINS.2018.8510581&partnerID=40&md5=d20869dec47e2f9cee34be40bdbea6e8
relation: 10.1109/ICCOINS.2018.8510581
identifier: 10.1109/ICCOINS.2018.8510581