Beschreibung:
The book talks about Bayesian Reasoning and Gaussian Processes in machine learning applications. It contains recent advancement in machine learning and highlights the applications of machine learning algorithms. This book is primarily aimed at graduates, researchers and professionals in the field of data science and machine learning.
1. Introduction to Naive Bayes and a Review on Its Subtypes with Applications 2. A Review on the Different Regression Analysis in Supervised Learning 3. Methods to Predict the Performance Analysis of Various Machine Learning Algorithms 4. A Viewpoint on Belief Networks and Their Applications 5. Reinforcement Learning Using Bayesian Algorithms with Applications 6. Alerting System for Gas Leakage in Pipelines 7. Two New Nonparametric Models for Biological Networks 8. Generating Various Types of Graphical Models via MARS 9. Financial Applications of Gaussian Processes and Bayesian Optimization 10. Bayesian Network Inference on Diabetes Risk Prediction Data