Bayesian reasoning and Gaussian processes for machine learning applications / edited by Hemachandran K., Shubham Tayal, Preetha Mary George, Parveen Singla, Utku Kose.
"The book Bayesian Reasoning and Gaussian Processes for Machine Learning Applications talks about Bayesian Reasoning and Gaussian Processes in machine learning applications. Bayesian methods are applied in many areas such as game development, decision making and drug discovery. It is very effec...
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| Online Access: |
Full Text (via Taylor & Francis) |
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| Other Authors: | , , , , |
| Format: | eBook |
| Language: | English |
| Published: |
Boca Raton, FL :
Chapman & Hall/CRC Press,
2022.
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| Edition: | First edition. |
| Subjects: |
Table of Contents:
- 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.