| 期刊全稱(chēng) | Applied Predictive Modeling | | 影響因子2023 | Max Kuhn,Kjell Johnson | | 視頻video | http://file.papertrans.cn/161/160057/160057.mp4 | | 發(fā)行地址 | Book specializes in data analysis with focus on practice of predictive modeling.Useful as a guide for practitioners.Reader can reproduce all results using R.Includes supplementary material: | | 圖書(shū)封面 |  | | 影響因子 | .Applied Predictive Modeling. covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. The text illustrates all parts of the modeling process through many hands-on, real-life examples, and every chapter contains extensive R code for each step of the process.?.This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses.? To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package..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 | | Pindex | Textbook 2013 |
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