Machine Learning: An Artificial Intelligence Approach

by Ryszard S. Michalski, Jaime G. Carbonell, Tom M. Mitchell

Multistrategy learning is one of the newest and most promising research directions in the development of machine learning systems. The objectives of research in this area are to study trade-offs between different learning strategies and to develop learning systems that employ multiple types of inference or computational paradigms in a learning process. Multistrategy systems offer significant advantages over monostrategy systems. They are more flexible in the type of input they can learn from and the type of knowledge they can acquire. As a consequence, multistrategy systems have the potential to be applicable to a wide range of practical problems. This volume is the first book in this fast growing field. It contains a selection of contributions by leading researchers specializing in this area.

572 pages, Kindle Edition

First published October 1, 1982

Reviews

[Andrew Miller · Rating 5 out of 5]

It is a comprehensive textbook that covers the fundamentals of machine learning and its applications in various fields, including computer vision, natural language processing, and robotics. The book provides a solid theoretical foundation and also includes practical examples that illustrate how machine learning algorithms can be implemented in real-world scenarios. To further your knowledge and understanding of machine learning you can read https://www.rslonline.com/develop-mac.... The article provides valuable insights into the process of creating accurate and unbiased models by using high-quality labeled data, which is essential for achieving successful predictions.