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Applied Predictive Modeling读书介绍

类别 页数 译者 网友评分 年代 出版社
书籍 600页 9.4 2020 Springer
定价 出版日期 最近访问 访问指数
USD 89.95 2020-02-20 … 2020-03-03 … 33
主题/类型/题材/标签
机器学习,统计学,R,数据挖掘,MachineLearning,数学,统计,数据科学,
作者
Max Kuhn      ISBN:9781461468486    原作名/别名:《》
内容和作者简介
Applied Predictive Modeling摘要

This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have ...

作者简介

This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics. Dr. Kuhn is a Director of Non-Clinical Statistics at Pfizer Global R&D in Groton Connecticut. He has been applying predictive models in the pharmaceutical and diagnostic industries for over 15 years and is the author of a number of R packages. Dr. Johnson has more than a decade of statistical consulting and predictive modeling experience in pharmaceutical research and development. He is a co-founder of Arbor Analytics, a firm specializing in predictive modeling and is a former Director of Statistics at Pfizer Global R&D. His scholarly work centers on the application and development of statistical methodology and learning algorithms.

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