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Algorithmic Learning in a Random World (Hardcover, 2005 ed.): Vladimir Vovk, Alex Gammerman, Glenn Shafer Algorithmic Learning in a Random World (Hardcover, 2005 ed.)
Vladimir Vovk, Alex Gammerman, Glenn Shafer
R4,653 Discovery Miles 46 530 Ships in 12 - 17 working days

Algorithmic Learning in a Random World describes recent theoretical and experimental developments in building computable approximations to Kolmogorov's algorithmic notion of randomness. Based on these approximations, a new set of machine learning algorithms have been developed that can be used to make predictions and to estimate their confidence and credibility in high-dimensional spaces under the usual assumption that the data are independent and identically distributed (assumption of randomness). Another aim of this unique monograph is to outline some limits of predictions: The approach based on algorithmic theory of randomness allows for the proof of impossibility of prediction in certain situations. The book describes how several important machine learning problems, such as density estimation in high-dimensional spaces, cannot be solved if the only assumption is randomness.

Causal Models and Intelligent Data Management (Hardcover, 1999 ed.): Alex Gammerman Causal Models and Intelligent Data Management (Hardcover, 1999 ed.)
Alex Gammerman
R1,579 Discovery Miles 15 790 Ships in 12 - 17 working days

The need to electronically store, manipulate and analyze large-scale, high-dimensional data sets requires new computational methods. This book presents new intelligent data management methods and tools, including new results from the field of inference. Leading experts also map out future directions of intelligent data analysis. This book will be a valuable reference for researchers exploring the interdisciplinary area between statistics and computer science as well as for professionals applying advanced data analysis methods in industry.

Causal Models and Intelligent Data Management (Paperback, Softcover reprint of the original 1st ed. 1999): Alex Gammerman Causal Models and Intelligent Data Management (Paperback, Softcover reprint of the original 1st ed. 1999)
Alex Gammerman
R1,441 Discovery Miles 14 410 Ships in 10 - 15 working days

Data analysis and inference have traditionally been research areas of statistics. However, the need to electronically store, manipulate and analyze large-scale, high-dimensional data sets requires new methods and tools, new types of databases, new efficient algorithms, new data structures, etc. - in effect new computational methods.
This monograph presents new intelligent data management methods and tools, such as the support vector machine, and new results from the field of inference, in particular of causal modeling. In 11 well-structured chapters, leading experts map out the major tendencies and future directions of intelligent data analysis. The book will become a valuable source of reference for researchers exploring the interdisciplinary area between statistics and computer science as well as for professionals applying advanced data analysis methods in industry and commerce. Students and lecturers will find the book useful as an introduction to the area.

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