Concepts of statistical learning and classification in machine learning: An overview

Open Access

Issue		BIO Web Conf. Volume 97, 2024 Fifth International Scientific Conference of Alkafeel University (ISCKU 2024)


Article Number		00129
Number of page(s)		21
DOI		https://doi.org/10.1051/bioconf/20249700129
Published online		05 April 2024

U.V. Luxburg and B. Scholkopf, “Statistical Learning Theory: Models, Concepts, and Results,” Max Planck Institute for Biological Cybernetics, Tubingen, Germany, 2008. [Google Scholar]
“Indian Institute of Technology Madras,” CS6464: Concepts In Statistical Learning Theory, January - May 2023. [Online]. Available: http://www.cse.iitm.ac.in/~vplab/statistical_learning_theory.html. [Google Scholar]
J. Xiong, “datacamp,” An Introduction to Statistical Machine Learning, Jun 2023. [Online]. Available: https://www.datacamp.com/tutorial/unveiling-the-magic-of-statistical-machine-learning. [Google Scholar]
J. Gimpel, “Medium / Published in Towards Data Science,” Statistical Learning Theory / The basis for neural networks, 26 Jul 2022. [Online]. Available: https://towardsdatascience.com/statistical-learning-theory-26753bdee66e. [Google Scholar]
J.P. Mueller and L. Massaron, Machine Learning For Dummies, Hoboken, New Jersey: John Wiley & Sons, Inc, 2016. [Google Scholar]
“javatpoint.com,” Machine Learning, [Online]. Available: https://www.javatpoint.com/machine-learning. [Accessed 6 feb 2023]. [Google Scholar]
O. Theobald, Machine Learning For Absolute Beginners, London, UK: Scatterplot press, 2017. [Google Scholar]
M.A. Ponti and R.F. MELLO, Machine Learning: A Practical Approach on the Statistical Learning Theory, Springer International Publishing, 2018. [Google Scholar]
S. Theodoridis, Machine Learning A Bayesian and Optimization Perspective, Elsevier Ltd, 2020. [Google Scholar]
M.L. Tut, “MLTut,” What is Machine Learning? Clear Your All Doubts Easily, [Online]. Available: https://www.mltut.com/what-is-machine-learning-clear-your-all-doubts-easily/. [Google Scholar]
I.H. Sarker, “Machine Learning: Algorithms, Real-World Applications and Research,” SN Computer Science, vol. 2, no. 160, pp. 1–21, 8 March 2021. [Google Scholar]
M. Swamynathan, Mastering Machine Learning with Python in Six Steps: A Practical Implementation Guide to Predictive Data Analytics Using Python, Bangalore, Karnataka, India: Manohar Swamynathan, 2017. [Google Scholar]
M.A. Hall, E. Frank and I.H. Witten, Data Mining Practical Machine Learning Tools and Techniques, Elsevier Science, 2011. [Google Scholar]
N.H. Ali, M. Emaduldeen and A.E. Ali, “Learning Evolution: a Survey,” Iraqi Journal of Science, vol. 62, no. 12, pp. 4978–4987, 2021. [CrossRef] [Google Scholar]
S.M. Alnedawe and H.K. Aljobouri, “A New Model Design for Combating, C.O.VID -19 Pandemic Based on SVM and CNN Approaches,” Baghdad Science Journal, vol. 20, no. 4, pp. 1402–1413, 2023. [Google Scholar]
databricks, “databricks,” Machine Learning Models, [Online]. Available: https://www.databricks.com/glossary/machine-learning-models. [Google Scholar]
K. Thiruvengadam, B. Watson, P. Chinnaiyan and R. Krishnan, “A Review of Statistical Modelling and Machine Learning in Analytical Problems,” International Journal of Applied Engineering Research, vol. 17, no. 5, pp. 506–510, 2022. [CrossRef] [Google Scholar]
C.P. Verma, S. Arora and A. Jain, “Machine Learning in Healthcare: Separating myth from reality,” International Journal of Advanced Science and Technology, vol. 29, no. 8, pp. 1348–1355, 2020. [Google Scholar]
J. Brownlee, “machine learning mastery,” 14 Different Types of Learning in Machine Learning, 11 Nov 2019. [Online]. Available: https://machinelearningmastery.com/types-of-learning-in-machine-learning/. [Google Scholar]
Domo, “Domo,” MACHINE LEARNING AND STATISTICAL INFERENCE The difference between machine learning and statistical inference, [Online]. Available: https://www.domo.com/glossary/what-is-machine-learning-and-statistical-inference. [Google Scholar]
S.N. Dhage and C.K. Raina, “A review on Machine Learning Techniques,” International Journal on Recent and Innovation Trends in Computing and Communication, vol. 4, no. 3, pp. 395–399, 2016. [Google Scholar]
A. Ram and Meenakshi, “Short Review on Machine Learning andits Application,” SPECIALUSIS UGDYMAS / SPECIAL EDUCATION, vol. 43, no. 1, pp. 9894–9902, 2022. [Google Scholar]
R. Raj, “enjoy algorithms,” Different Types of Machine Learning Models, [Online]. Available: https://www.enjoyalgorithms.com/blog/classification-of-machine-learning-models. [Google Scholar]
R. Tibshirani, T. Hastie, D. Witten and G. James, An Introduction to Statistical Learning With Applications in R, Springer New York, 2013. [Google Scholar]
S. Ray, “A Quick Review of Machine Learning Algorithms,” in 2019 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (Com-IT-Con), India, 14th -16th Feb 2019, India, 2019. [Google Scholar]
M. Waseem, “Edureka Blog,” How To Implement Classification In Machine Learning?, 2 Aug 2023. [Online]. Available: https://www.edureka.co/blog/classification-in-machine-learning/. [Google Scholar]
J. Brownlee, “Machine Learning Mastery,” 4 Types of Classification Tasks in Machine Learning, 19 Aug 2020. [Online]. Available: https://machinelearningmastery.com/types-of-classification-in-machine-learning/. [Google Scholar]
S. Gupta, “Springboard,” Regression vs. Classification in Machine Learning: What’s the Difference?, 6 Oct. 2021. [Online]. Available: https://www.springboard.com/blog/data-science/regression-vs-classification/. [Google Scholar]
S. Dridi, “Unsupervised Learning - A SYSTEMATIC LITERATURE REVIEW,” 2021. [Online]. Available: https://files.osf.io/v1/resources/tysr4/providers/osfstorage/624a442a7a7d9e04500608ce?action=download&direct&version=3. [Google Scholar]
V. Rastogi, S. Satija, P.K. Sharma and S. Singh, “MACHINE LEARNING ALGORITHMS:OVERVIEW,” International Journal of Advanced Research in Engineering and Technology (IJARET), vol. 11, no. 9, pp. 512–517, 2020. [Google Scholar]
M. Shirsat, “Linkedin,” Semi-supervised Learning: Training Models with a Combination of Labeled and Unlabeled Data, 28 Mar 2023. [Online]. Available: https://www.linkedin.com/pulse/semi-supervised-learning-training-models-combination-labeled-shirsat. [Google Scholar]
Tech Vidvan, “TechVidvan,” Reinforcement Learning Algorithms and Applications, [Online]. Available: https://techvidvan.com/tutorials/reinforcement-learning/. [Google Scholar]
D. Parrochia, “Mathematical Theory of Classification,” Knowledge Organization, vol. 44, no. 7, pp. 184–201, 2017. [Google Scholar]
“University of Minnesota/ Classification: Basic Concepts and Techniques,” [Online]. Available: https://www-users.cse.umn.edu/~kumar001/dmbook/ch3_classification.pdf. [Google Scholar]
D. Michie, D.J. Spiegelhalter and C.C. Taylor, Machine Learning, Neural and Statistical, February 17, 1994. [Google Scholar]
Z. Keita, “datacamp,” Classification in Machine Learning: An Introduction, Sep 2022. [Online]. Available: https://www.datacamp.com/blog/classification-machine-learning. [Google Scholar]
M. Krintus, M. Koziński, M.K. Prusińska, E. Laskowska, E. Janiszewska, J. Kubica and G.O. Sypniewska, “The performance of triglyceride to high-density lipoprotein cholesterol ratio in acute coronary syndromes using a diagnostic decision tree,” Folia Medica Copernicana, vol. 3, no. 1, pp. 13–19, 2015. [Google Scholar]
S. Bansal, “ANALYTIXLABS,” MACHINE LEARNING What is Classification Algorithm in Machine Learning? With Examples, 25 JANUARY 2023. [Online]. Available: https://www.analytixlabs.co.in/blog/classification-in-machine-learning/. [Google Scholar]
C. Goyal, “Analytics Vidhya,” Demystifying the Difference Between Multi-Class and Multi-Label Classification Problem Statements in Deep Learning, 26 Aug 2021. [Online]. Available: https://www.analyticsvidhya.com/blog/2021/07/demystifying-the-difference-between-multi-class-and-multi-label-classification-problem-statements-in-deep-learning/. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.