The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Introduction to Machine Learning
Abstract
Machine learning refers to the changes in systems that perform tasks associated with artificial intelligence. This chapter presents introduction types and application of machine learning. This chapter also presents the basic concepts related to feature selection techniques such as filter, wrapper and hybrid methods and various machine learning techniques such as artificial neural network, Naive Bayes classifier, support vector machine, k-nearest-neighbor, decision trees, bagging, boosting, random subspace method, random forests, k-means clustering and deep learning. In the last the performance measure of the classifier is presented.
Related Content
Dankan Gowda V., Anjali Sandeep Gaikwad, Pilli Lalitha Kumari, Erdal Buyukbicakci, Sengul Ibrahimoglu.
© 2025.
32 pages.
|
Debasish Banerjee, Ranjit Barua, Sudipto Datta, Dileep Pathote.
© 2025.
18 pages.
|
Kok Yeow You, Man Seng Sim.
© 2025.
96 pages.
|
Man Seng Sim, Kok Yeow You, Fahmiruddin Esa, Raimi Dewan, DiviyaDevi Paramasivam, Rozeha A. Rashid.
© 2025.
38 pages.
|
Mandeep Kaur.
© 2025.
24 pages.
|
Ganesh Khekare, Priya Dasarwar, Ajay Kumar Phulre, Urvashi Khekare, Gaurav Kumar Ameta, Shashi Kant Gupta.
© 2025.
22 pages.
|
Manoj Kumar Elipey, P. S. Kishore, Ratna Sunil Buradagunta.
© 2025.
14 pages.
|
|
|