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
来源
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON SOFT COMPUTING SYSTEMS, ICSCS 2015, VOL 1 | 2016年 / 397卷
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
  • [31] Algorithms: Supervised Machine Learning Types and Their Application Domains
    Divyashree, N.
    Prasad, K. S. Nandini
    PROCEEDINGS OF SECOND INTERNATIONAL CONFERENCE ON SUSTAINABLE EXPERT SYSTEMS (ICSES 2021), 2022, 351 : 787 - 807
  • [32] Evaluation of Machine Learning Algorithms for Automatic Modulation Recognition
    Hazar, Muhammed Abdurrahman
    Odabasioglu, Niyazi
    Ensari, Tolga
    Kavurucu, Yusuf
    NEURAL INFORMATION PROCESSING, PT I, 2015, 9489 : 208 - 215
  • [33] Detection of Stroke Disease using Machine Learning Algorithms
    Shoily, Tasfia Ismail
    Islam, Tajul
    Jannat, Sumaiya
    Tanna, Sharmin Akter
    Alif, Taslima Mostafa
    Ema, Romana Rahman
    2019 10TH INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION AND NETWORKING TECHNOLOGIES (ICCCNT), 2019,
  • [34] Computational Complexity and Analysis of Supervised Machine Learning Algorithms
    Singh, Jarnail
    NEXT GENERATION OF INTERNET OF THINGS, 2023, 445 : 195 - 206
  • [35] Long-Term-Based Road Blackspot Screening Procedures by Machine Learning Algorithms
    Fiorentini, Nicholas
    Losa, Massimo
    SUSTAINABILITY, 2020, 12 (15)
  • [36] Effective Selection of Machine Learning Algorithms for Big Data Analytics Using Apache Spark
    Hafez, Manar Mohamed
    Shehab, Mohamed Elemam
    El Fakharany, Essam
    Hegazy, Abd El Ftah Abdel Ghfar
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT SYSTEMS AND INFORMATICS 2016, 2017, 533 : 692 - 704
  • [37] Machine learning algorithms for dengue risk assessment: a case study for Sao Luis do Maranhao
    Rocha, Fernanda Paula
    Giesbrecht, Mateus
    COMPUTATIONAL & APPLIED MATHEMATICS, 2022, 41 (08)
  • [38] Heart Disease Prediction Using Core Machine Learning Techniques-A Comparative Study
    Sarah, Sfurti
    Gourisaria, Mahendra Kumar
    Khare, Sandali
    Das, Himansu
    ADVANCES IN DATA AND INFORMATION SCIENCES, 2022, 318 : 247 - 260
  • [39] Ad Click Fraud Detection Using Machine Learning and Deep Learning Algorithms
    Alzahrani, Reem A.
    Aljabri, Malak
    Mohammad, Rami A. Mustafa
    IEEE ACCESS, 2025, 13 : 12746 - 12763
  • [40] A Comparative Study of Machine Learning Algorithms for Prior Prediction of UFC Fights
    Hitkul
    Aggarwal, Karmanya
    Yadav, Neha
    Dwivedy, Maheshwar
    HARMONY SEARCH AND NATURE INSPIRED OPTIMIZATION ALGORITHMS, 2019, 741 : 67 - 76