Predicting Liver Cirrhosis Stages Using Extra Trees, Random Forest, and SVM with Data Mining Techniques

被引:0
|
作者
Ali, Duaa S. [1 ]
Aljabery, Maalim A. [1 ]
机构
[1] Faculty of Computer Science & Information Technology, Computer Science Dept, University of Basrah, Basrah, Iraq
来源
Informatica (Slovenia) | 2024年 / 48卷 / 21期
关键词
All Open Access; Gold;
D O I
10.31449/inf.v48i21.6752
中图分类号
学科分类号
摘要
Support vector machines
引用
收藏
页码:15 / 26
相关论文
共 50 条
  • [41] Comparision using Data Mining Algorithm Techniques for Predicting of Dengue fever Data in Northeastern of Thailand
    Jongmuenwai, Benjapuk
    Lowanichchai, Sudajai
    Jabjone, Saisunee
    2018 15TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING/ELECTRONICS, COMPUTER, TELECOMMUNICATIONS AND INFORMATION TECHNOLOGY (ECTI-CON), 2018, : 532 - 535
  • [42] What is the best predictor of word difficulty? A case of data mining using random forest
    Ha, Hung Tan
    Nguyen, Duyen Thi Bich
    Stoeckel, Tim
    LANGUAGE TESTING, 2024, 41 (04) : 828 - 844
  • [43] MINING STUDENT'S ADMISSION DATA AND PREDICTING STUDENT'S PERFORMANCE USING DECISION TREES
    Asif, R.
    Merceron, A.
    Pathan, M. K.
    5TH INTERNATIONAL CONFERENCE OF EDUCATION, RESEARCH AND INNOVATION (ICERI 2012), 2012, : 5121 - 5129
  • [44] Churn prediction in digital game-based learning using data mining techniques: Logistic regression, decision tree, and random forest
    Kiguchi, Mai
    Saeed, Waddah
    Medi, Imran
    APPLIED SOFT COMPUTING, 2022, 118
  • [45] A Predictive Model to identify possible affected Bipolar disorder students using Naive Baye's, Random Forest and SVM machine learning techniques of data mining and Building a Sequential Deep Learning Model using Keras
    Peerbasha, S.
    Surputheen, M. Mohamed
    INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY, 2021, 21 (05): : 267 - 274
  • [46] Predicting Transitional Interval of Kidney Disease Stages 3 to 5 Using Data Mining Method
    Panwong, Patcharaporn
    Iam-On, Natthakan
    2016 SECOND ASIAN CONFERENCE ON DEFENCE TECHNOLOGY (ACDT), 2016, : 145 - 150
  • [47] Predicting the postmortem interval using human intestinal microbiome data and random forest algorithm
    Hu, Lai
    Xing, Yu
    Jiang, Pu
    Gan, Li
    Zhao, Fan
    Peng, Wenli
    Li, Weihan
    Tong, Yanqiu
    Deng, Shixiong
    SCIENCE & JUSTICE, 2021, 61 (05) : 516 - 527
  • [48] Advanced data mining techniques and how to build and interpret treenet/mart and random forests models: The evolution of data mining from cart to ensembles of trees.
    Golovnya, M.
    AMERICAN JOURNAL OF EPIDEMIOLOGY, 2006, 163 (11) : S25 - S25
  • [49] Preliminary Big Data Analytics of Hepatitis Disease by Random Forest and SVM Using R- Tool
    Lakshmi, Visali P. R.
    Shwetha, G.
    Raja, N. Madhava
    2017 THIRD INTERNATIONAL CONFERENCE ON BIOSIGNALS, IMAGES AND INSTRUMENTATION (ICBSII), 2017,
  • [50] Predicting the Probability of Student's Degree Completion by Using Different Data Mining Techniques
    Ahuja, Ravinder
    Kankane, Yash
    2017 FOURTH INTERNATIONAL CONFERENCE ON IMAGE INFORMATION PROCESSING (ICIIP), 2017, : 474 - 477