统计学习方法-李航 PDF 分享

统计学习方法

统计学习方法-李航 PDF

统计学习方法-李航 PDF
统计学习方法-李航 PDF

统计学习是计算机及其应用领域的一门重要学科。

统计学习方法全面系统地介绍了统计学习的主要方法,特别是监督学习方法,包括感知器、k近邻法、朴素贝叶斯法、决策树、logistic回归和支持向量机、提升法、EM算法、隐马尔可夫模型和条件场。

除了以下章节的介绍和总结外,每章还介绍了一种方法。叙述从具体问题或实例入手,由浅入深地阐明观点,并进行必要的数学推导,使读者能够掌握统计学习方法的本质并学会使用。

为了满足读者进一步学习的需要,本书还介绍了一些相关研究,给出了少量练习,并列出了主要参考文献。

《统计学习方法》是统计学习及相关课程的教学参考书。适用于文档数据挖掘、信息检索和自然语言处理专业的大学生和研究生,以及计算机应用专业的研发人员。

Statistical learning is an important subject in the field of computer and its application.

Statistical learning methods comprehensively and systematically introduces the main methods of statistical learning, especially supervised learning methods, including perceptron, k-nearest neighbor method, naive Bayesian method, decision tree, logistic regression and support vector machine, lifting method, EM algorithm, hidden Markov model and conditional field.

In addition to the introduction and summary of the following chapters, each chapter also introduces a method. The narration starts with specific problems or examples, clarifies views from simple to deep, and makes necessary mathematical derivation, so that readers can master the essence of statistical learning methods and learn to use them.

In order to meet the needs of readers for further study, this book also introduces some relevant research, gives a small number of exercises, and lists the main references.

Statistical learning methods is a teaching reference book for statistical learning and related courses. It is suitable for college and graduate students majoring in document data mining, information retrieval and natural language processing, as well as R & D personnel majoring in computer applications.

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