Edited Z83 Form
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Flood Risk Management (Scotland) Act 2009
Flood Risk Management (Scotland) Act 2009, written by HM Government describes about to make provision about the assessment and sustainable management of flood risks.
The Nature of Statistical Learning Theory
Author: Vladimir Vapnik
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-06-29
The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics. These include: * the setting of learning problems based on the model of minimizing the risk functional from empirical data * a comprehensive analysis of the empirical risk minimization principle including necessary and sufficient conditions for its consistency * non-asymptotic bounds for the risk achieved using the empirical risk minimization principle * principles for controlling the generalization ability of learning machines using small sample sizes based on these bounds * the Support Vector methods that control the generalization ability when estimating function using small sample size. The second edition of the book contains three new chapters devoted to further development of the learning theory and SVM techniques. These include: * the theory of direct method of learning based on solving multidimensional integral equations for density, conditional probability, and conditional density estimation * a new inductive principle of learning. Written in a readable and concise style, the book is intended for statisticians, mathematicians, physicists, and computer scientists. Vladimir N. Vapnik is Technology Leader AT&T Labs-Research and Professor of London University. He is one of the founders of
ICPC-2-R
This fully revised and corrected edition of the International Classification of Primary Care 2e (ICPC-2) is indispensable for anyone wishing to use the international classification system for classificaton of morbidity data in a primary care setting. The concept of ICPC-2 has not been changed but the main body of the actual classification (chapter 10) has been completely revised to reflect the adequate use for an individual patient record and for research purposes. This now brings the printed version of ICPC-2 completely in-line with the electronic version previously only available through the Oxford Website for the journal Family Practice. ICPC-2 is patient-oriented rather than disease or provider-oriented. It encompasses both the patient's reason for encounter and the patient's problem. ICPC-2 is extensively used internationally and includes a detailed conversion system for linking the ICPC and ICD-10 codes published by WHO, additional inclusion criteria, and cross-referencing rubrics. ICPC-2 It has been developed based on the recognition that building the appropriate primary care systems to allow the assessment and implementation of health care priorities is possible only if the right information is available to health care planners.