Predicting Structured Data артикул 190e.
Predicting Structured Data артикул 190e.

Редакторы: Gokhan H Bakir Thomas Hofmann Bernhard Scholkopf Александер Дж Смола Ben Taskar S V N Vishwanathan Machine learning develops intelligent computer systems that are able to generalize from previously seen examples A new domain of machine learning, in which the prediction must satisfy the additional constraints озснъ found in structured data, poses one of machine learning’s greatest challenges: learning functional dependencies between arbitrary input and output domains This volume presents and analyzes the state of the art in machine learning algorithms and theory in this novel field The contributors discuss applications as diverse as machine translation, document markup, computational biology, and information extraction, among others, providing a timely overview of an exciting field.  Стильно оформленноеИздательство: The MIT Press, 2007 г Твердый переплет, 360 стр ISBN 0262026171 Язык: Английский.