PML: A parallel machine learning toolbox for data classification and regression

被引：0
|
作者：
Jing, Runyu [1 ]
Sun, Jing [1 ]
Wang, Yuelong [1 ]
Li, Menglong [1 ]
Pu, Xuemei [1 ]
机构：
[1] College of Chemistry, Sichuan University, Chengdu,610064, China
来源：
Chemometrics and Intelligent Laboratory Systems | 2014年 / 138卷
基金：
中国国家自然科学基金;
关键词：
Computer operating systems - Learning systems - Open source software - Open systems - Regression analysis;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Motivated by timesaving when dealing with the large-scale calculation for data modeling in parallel with multiple CPU cores or machines and result comparison, PML was designed in this study. PML has the ability to do dimension reduction and grid search in parallel, support both classification and regression, and could generate HTML pages as output for results comparison. Written in PERL, PML is compatible with Windows and Linux. This open source software is free available together with the code, manual, examples and license from http://cic.scu.edu.cn/pml or https://github.com/limlcic/PML. te related analysis. This software supports both classification and regression. © 2014 Elsevier B.V.
引用
收藏
页码：1 / 6
相关论文
共 50 条
  • [1] PML: A parallel machine learning toolbox for data classification and regression
    Jing, Runyu
    Sun, Jing
    Wang, Yuelong
    Li, Menglong
    Pu, Xuemei
    CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2014, 138 : 1 - 6
  • [2] PML: A parallel machine learning toolbox for data classification and regression
    Jing, Runyu
    Sun, Jing
    Wang, Yuelong
    Li, Menglong
    Pu, Xuemei
    Chemometrics and Intelligent Laboratory Systems, 2014, 138 : 1 - 6
  • [3] Data Provenance Based System for Classification and Linear Regression in Distributed Machine Learning
    Khan, Muhammad Jahanzeb
    Wang, Ruoyu
    Sun, Daniel
    Li, Guoqiang
    STRUCTURED OBJECT-ORIENTED FORMAL LANGUAGE AND METHOD (SOFL+MSVL 2019), 2020, 12028 : 279 - 295
  • [4] Review of Machine Learning Classifier Toolbox of Neuroimaging Data
    Lad, Rashmi
    Metkewar, P. S.
    2020 IEEE PUNE SECTION INTERNATIONAL CONFERENCE (PUNECON), 2020, : 175 - 179
  • [5] Functional extreme learning machine for regression and classification
    Liu, Xianli
    Zhou, Yongquan
    Meng, Weiping
    Luo, Qifang
    MATHEMATICAL BIOSCIENCES AND ENGINEERING, 2023, 20 (02) : 3768 - 3792
  • [6] Extreme Learning Machine for Regression and Multiclass Classification
    Huang, Guang-Bin
    Zhou, Hongming
    Ding, Xiaojian
    Zhang, Rui
    IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2012, 42 (02): : 513 - 529
  • [7] Sparse Least-Squares Methods in the Parallel Machine Learning (PML) Framework
    Natarajan, Ramesh
    Sindhwani, Vikas
    Tatikonda, Shirish
    2009 IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW 2009), 2009, : 314 - +
  • [8] Parallel extreme learning machine for regression based on MapReduce
    He, Qing
    Shang, Tianfeng
    Zhuang, Fuzhen
    Shi, Zhongzhi
    NEUROCOMPUTING, 2013, 102 : 52 - 58
  • [9] MVPAlab: A machine learning decoding toolbox for multidimensional electroencephalography data
    Lopez-Garcia, David
    Penalver, Jose M. G.
    Gorriz, Juan M.
    Ruz, Maria
    COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2022, 214
  • [10] Data Center Predictions using MATLAB Machine Learning Toolbox
    Levy, Moises
    Raviv, Daniel
    Baker, Justin
    2019 IEEE 9TH ANNUAL COMPUTING AND COMMUNICATION WORKSHOP AND CONFERENCE (CCWC), 2019, : 458 - 464
12345