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Who Should Read this Book
This book is designed for researchers and students in a broad variety of
fields: statistics, artificial intelligence, engineering, finance and others. We
expect that the reader will have had at least one elementary course in
statistics, covering basic topics including linear regression.
We have not attempted to write a comprehensive catalog of learning
methods, but rather to describe some of the most important techniques.
Equally notable, we describe the underlying concepts and considerations
by which a researcher can judge a learning method. We have tried to write
this book in an intuitive fashion, emphasizing concepts rather than math-
ematical details.
As statisticians, our exposition will naturally reflect our backgrounds and
areas of expertise. However in the past eight years we have been attending
conferences in neural networks, data mining and machine learning, and our
thinking has been heavily influenced by these exciting fields. This influence
is evident in our current research, and in this book.
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