Format:
1 Online-Resource (147 Seiten)
Edition:
First edition
ISBN:
9781003164265
,
1003164269
,
9781000569599
,
1000569594
,
9781000569582
,
1000569586
Content:
Introduction to naive Bayes and a review on its subtypes with applications / Eguturi Manjith Kumar Reddy, Akash Gurrala, Vasireddy Bindu Hasitha, Korupalli V. Rajesh Kumar -- A review on different regression analysis in supervised learning / K. Sudhaman, Mahesh Akuthota and Sandip Kumar Chaurasiya -- Methods to predict the performance analysis of various machine learning algorithms / M. Saritha, M. Lavanya and M. Narendra Reddy -- A viewpoint on belief networks and their applications / G.S. Sivakumar, P. Suneetha, V. Sailaja and Pokala Pranay Kumar -- Reinforcement learning using Bayesian algorithms with applications / H. Raghupathi, G. Ravi and Rajan Maduri -- Alerting system for gas leakage in pipeline / Nilesh Deotale, Pragya Chandra, Prathamesh Dherange, Pratiksha Repaswal, Saibaba V. More -- New non-parametric models for biological networks / Deniz Seçilmiş, Melih Ağraz, Vilda Purutçuoğlu -- Generating various types of graphical models via MARS / Ezgi Ayyıldız and Vilda Purutçuoğlu -- Financial applications of Gaussian processes and Bayesian optimization / Syed Hasan Jafar -- Bayesian network inference on diabetes risk prediction data / Mustafa Özgür Cingiz.
Additional Edition:
ISBN 9780367758479
Additional Edition:
ISBN 9780367758493
Additional Edition:
Erscheint auch als Druck-Ausgabe Bayesian reasoning and Gaussian processes for machine learning applications Boca Raton, FL : CRC Press, Taylor & Francis Group, 2022 ISBN 9780367758479
Additional Edition:
ISBN 9780367758493
Language:
English
DOI:
10.1201/9781003164265
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