This book is a practical guide to classification learning systems and their applications. These computer programs learn from sample data and make predictions for new cases, sometimes exceeding the performance of humans.
Practical learning systems from statistical pattern recognition, neural networks, and machine learning are presented. The authors examine prominent methods from each area, using an engineering approach and taking the practitioner's viewpoint. Intuitive explanations with a minimum of mathematics make the material accessible to anyone--regardless of experience or special interests.
The underlying concepts of the learning methods are discussed with fully worked-out examples: their strengths and weaknesses, and the estimation of their future performance on specific applications. Throughout, the authors offer their own recommendations for selecting and applying learning methods such as linear discriminants, back-propagation neural networks, or decision trees. Learning systems are then contrasted with their rule-based counterparts from expert systems.
- ISBN10 1558600655
- ISBN13 9781558600652
- Publish Date 28 December 1990
- Publish Status Out of Print
- Out of Print 21 November 2009
- Publish Country US
- Publisher Elsevier Science & Technology
- Imprint Morgan Kaufmann Publishers In
- Format Hardcover
- Pages 223
- Language English