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Hand David

    David J. Hand est un mathématicien et auteur distingué dont le travail explore les principes de la probabilité et de l'analyse des données. Son expertise couvre un large éventail de sujets, de la classification et de l'exploration de données aux fondements de la statistique. À travers ses publications, il examine comment les modèles statistiques influencent notre perception du monde et comment découvrir des événements apparemment improbables. L'approche de Hand repose sur une profonde compréhension des principes mathématiques et de leur application aux phénomènes du monde réel.

    Statistics: A Very Short Introduction
    The Improbability Principle
    Principles of Data Mining
    • Principles of Data Mining

      • 578pages
      • 21 heures de lecture
      3,8(28)Évaluer

      The first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics.The growing interest in data mining is motivated by a common problem across disciplines: how does one store, access, model, and ultimately describe and understand very large data sets? Historically, different aspects of data mining have been addressed independently by different disciplines. This is the first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics.The book consists of three sections. The first, foundations, provides a tutorial overview of the principles underlying data mining algorithms and their application. The presentation emphasizes intuition rather than rigor. The second section, data mining algorithms, shows how algorithms are constructed to solve specific problems in a principled manner. The algorithms covered include trees and rules for classification and regression, association rules, belief networks, classical statistical models, nonlinear models such as neural networks, and local memory-based models. The third section shows how all of the preceding analysis fits together when applied to real-world data mining problems. Topics include the role of metadata, how to handle missing data, and data preprocessing.

      Principles of Data Mining
    • The Improbability Principle

      • 320pages
      • 12 heures de lecture
      3,5(54)Évaluer

      Why is it that incredibly unlikely phenomena actually happen quite regularly and why should we, in fact, expect such things to happen? Here, in this highly original book - aimed squarely at anyone with an interest in coincidences, probability or gambling - eminent statistician David Hand answers this question by weaving together various strands of probability into a unified explanation, which he calls the improbability principle. This is a book that will appeal not only to those who love stories about startling coincidences and extraordinarily rare events, but also to those who are interested in how a single bold idea links areas as diverse as gambling, the weather, airline disasters and creative writing as well as the origin of life and even the universe. The Improbability Principle will change your perspective on how the world works - and tell you what the Bible code and Shakespeare have in common, how to win the lottery, why Apple's song shuffling was made less random to seem more random. Oh and why lightning does in fact strike twice...

      The Improbability Principle
    • Statistics: A Very Short Introduction

      • 124pages
      • 5 heures de lecture
      3,5(409)Évaluer

      Statistics has evolved into an exciting discipline which uses deep theory and powerful software to shed light on the world around us: from clinical trials in medicine, to economics, sociology, and countless other subjects vital to understanding modern life. This Very Short Introduction explores and explains how statistics works today.

      Statistics: A Very Short Introduction