We recommend using a modern web browser such as Google Chrome or Microsoft Edge with their default settings.
READING ON THE GO AT UNION STATION LENDING LIBRARY
In the spring of 2015, The Union Station Redevelopment Corporation launched a […]
Hello, I'm an eBook!
ATTENTION: This item is an eBook. It can be read on iOS, Android, MAC and PC's with a supported eReader. It is not a physical book. eBooks are available via download immediately after you've checked out.
Shipped from other seller
May ship separately
Ships separately from Better World Books suppliers
Super Book Deals
In "Reliable Reasoning," Gilbert Harman and Sanjeev Kulkarni--a philosopher and an engineer--argue that philosophy and cognitive science can benefit from statistical learning theory (SLT), the theory that lies behind recent advances in machine learning. The philosophical problem of induction, for example, is in part about the reliability of inductive reasoning, where the reliability of a method is measured by its statistically expected percentage of errors--a central topic in SLT.
After discussing philosophical attempts to evade the problem of induction, Harman and Kulkarni provide an admirably clear account of the basic framework of SLT and its implications for inductive reasoning. They explain the Vapnik-Chervonenkis (VC) dimension of a set of hypotheses and distinguish two kinds of inductive reasoning. The authors discuss various topics in machine learning, including nearest-neighbor methods, neural networks, and support vector machines. Finally, they describe transductive reasoning and suggest possible new models of human reasoning suggested by developments in SLT.
Come shop our entire inventory of used books. Get discount code »
Gift Certificate = Happy Friend + Books donated to families in need. Make Someone Happy »
We match every book you purchase with a book donation. Learn more »
Sign up now to get news, sales and special promotions!
© Better World Books (BetterWorldBooks.com)