A Conjectural Study on Machine Learning Algorithms

被引:3
|
作者
Sankar, Abijith [1 ]
Bharathi, P. Divya [1 ]
Midhun, M. [1 ]
Vijay, K. [1 ]
Kumar, T. Senthil [1 ]
机构
[1] Amrita Vishwa Vidyapeetham, Amrita Sch Engn, Dept Comp Sci & Engn, Coimbatore, Tamil Nadu, India
关键词
Machine learning algorithms; Supervised learning; Unsupervised learning; Bagging; Boosting; KNN; Random forests; Logistic regression; Decision trees; Naive bayes; k-Means clustering; Partitional clustering; Divisive clustering; Hierarchical clustering; Agglomerative clustering;
D O I
10.1007/978-81-322-2671-0_10
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Artificial Intelligence, a field which deals with the study and design of systems, which has the capability of observing its environment and does functionalities which aims at maximizing the probability of its success in solving problems. AI turned out to be a field which captured wide interest and attention from the scientific world, so that it gained extraordinary growth. This in turn resulted in the increased focus on a field-which deals with developing the underlying conjectures of learning aspects and learning machines-machine learning. The methodologies and objectives of machine learning played a vital role in the considerable progress gained by AI. Machine learning aims at improving the learning capabilities of intelligent systems. This survey is aimed at providing a theoretical insight into the major algorithms that are used in machine learning and the basic methodology followed in them.
引用
收藏
页码:105 / 116
页数:12
相关论文
共 50 条
  • [1] Algorithms for Machine Learning
    Hsu, Daniel
    IEEE INTELLIGENT SYSTEMS, 2016, 31 (01) : 60 - 60
  • [2] Study of Machine Learning Algorithms for Detecting Web Bot
    Poptiphueng, Thanu
    Siribunyaphat, Nannaphat
    Sukpongthai, Warattha
    Moolwat, Onuma
    2024 21st International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2024, 2024,
  • [3] Application of machine learning algorithms in an epidemiologic study of mortality
    Agogo, George O.
    Mwambi, Henry
    ANNALS OF EPIDEMIOLOGY, 2025, 102 : 36 - 47
  • [4] A Comparative Study on Machine Learning Algorithms for Indoor Positioning
    Bozkurt, Sinem
    Elibol, Gulin
    Gunal, Serkan
    Yayan, Ugur
    2015 INTERNATIONAL SYMPOSIUM ON INNOVATIONS IN INTELLIGENT SYSTEMS AND APPLICATIONS (INISTA) PROCEEDINGS, 2015, : 47 - 54
  • [5] A Comparative Study on Machine Learning algorithms for Knowledge Discovery
    Suseela, Siddesh Sambasivam
    Feng, Yang
    Mao, Kezhi
    2022 17TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION (ICARCV), 2022, : 131 - 136
  • [6] An Empirical Study of Machine Learning Algorithms for Cancer Identification
    Turki, Turki
    2018 IEEE 15TH INTERNATIONAL CONFERENCE ON NETWORKING, SENSING AND CONTROL (ICNSC), 2018,
  • [7] Study of Machine Learning Algorithms for Detecting Web Bot
    Poptiphueng, Thanu
    Siribunyaphat, Nannaphat
    Sukpongthai, Warattha
    Moolwat, Onuma
    2024 21ST INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING/ELECTRONICS, COMPUTER, TELECOMMUNICATIONS AND INFORMATION TECHNOLOGY, ECTI-CON 2024, 2024,
  • [8] A comparative study of Machine learning algorithms for VANET networks
    Ftaimi, Sara
    Mazri, Tomader
    3RD INTERNATIONAL CONFERENCE ON NETWORKING, INFORMATION SYSTEM & SECURITY (NISS'20), 2020,
  • [9] Combinatorial algorithms in machine learning
    Shaw, Peter
    2018 FIRST IEEE INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE FOR INDUSTRIES (AI4I 2018), 2018, : 127 - 128
  • [10] Fair Algorithms for Machine Learning
    Kearns, Michael
    EC'17: PROCEEDINGS OF THE 2017 ACM CONFERENCE ON ECONOMICS AND COMPUTATION, 2017, : 1 - 1