Machine Learning : A Constraint-Based Approach (Paperback)

Marco Gori Ph.D.

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商品描述

Machine Learning: A Constraint-Based Approach provides readers with a refreshing look at the basic models and algorithms of machine learning, with an emphasis on current topics of interest that includes neural networks and kernel machines.

The book presents the information in a truly unified manner that is based on the notion of learning from environmental constraints. While regarding symbolic knowledge bases as a collection of constraints, the book draws a path towards a deep integration with machine learning that relies on the idea of adopting multivalued logic formalisms, like in fuzzy systems. A special attention is reserved to deep learning, which nicely fits the constrained- based approach followed in this book.

This book presents a simpler unified notion of regularization, which is strictly connected with the parsimony principle, and includes many solved exercises that are classified according to the Donald Knuth ranking of difficulty, which essentially consists of a mix of warm-up exercises that lead to deeper research problems. A software simulator is also included.

  • Presents fundamental machine learning concepts, such as neural networks and kernel machines in a unified manner
  • Provides in-depth coverage of unsupervised and semi-supervised learning
  • Includes a software simulator for kernel machines and learning from constraints that also includes exercises to facilitate learning
  • Contains 250 solved examples and exercises chosen particularly for their progression of difficulty from simple to complex

商品描述(中文翻譯)

《機器學習:基於約束的方法》為讀者提供了對機器學習基本模型和算法的全新觀點,重點關注當前感興趣的主題,包括神經網絡和核機器。

本書以從環境約束中學習的概念為基礎,以真正統一的方式呈現信息。在將符號知識庫視為約束集合的同時,本書提出了一條通往與機器學習深度融合的道路,該融合依賴於採用多值邏輯形式主義的想法,例如模糊系統。本書特別關注深度學習,這與本書所遵循的基於約束的方法非常契合。

本書提出了一個更簡單統一的正則化概念,與簡潔原則密切相關,並包含許多已解決的練習題,這些題目根據Donald Knuth的難度分級進行分類,基本上包括一系列引導更深入研究問題的熱身練習。書中還附有軟件模擬器。

本書以統一的方式介紹了基本的機器學習概念,如神經網絡和核機器。深入探討了無監督和半監督學習。包含了一個核機器和從約束中學習的軟件模擬器,並提供了練習題以促進學習。書中包含250個已解決的例題和練習題,這些題目根據難度從簡單到複雜進行了分類。