Predictive Analytics for Business Using R
Barton, Russell R.
- 出版商: World Scientific Pub
- 出版日期: 2024-09-20
- 售價: $5,100
- 貴賓價: 9.5 折 $4,845
- 語言: 英文
- 頁數: 464
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 9811293775
- ISBN-13: 9789811293771
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相關分類:
Machine Learning
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相關主題
商品描述
The fields of mathematical statistics, statistical graphics, computer science and operations research have created the rich set of methods now called Analytics. Often analytics is characterized along three poles: descriptive analytics (what do data tell us), predictive analytics (what can be forecast based on the data, and with what certainty), and prescriptive analytics (how can the data inform changes to improve system performance).This book focuses on the second pole, predictive analytics. The areas of predicting a number, a class, and dynamic behavior are distinct, with different methods. This text has three parts based on these areas. Topics in predicting a number include simple and multiple linear regression, transformation of variables, analysis of observational data via cross-validation, the generalized linear model, designed experiments, and Gaussian process and neural network regression. Classification methods include neural networks, logistic regression, k-nearest neighbor, and linear discriminant analysis. Methods for predicting dynamic behavior include trend analysis, time series analysis and discrete-event dynamic simulation.Characterizing prediction uncertainty is a key focus of this text. The text provides analytic methods appropriate to each area, with an explicit process for applying such methods. Case data with corresponding R code are used to illustrate each method.Predictive Analytics for Business using R is designed for a hybrid class structure. Class sessions can be a blend of lecture format and flipped classroom case analyses. In a two-meetings-per-week fifteen-week structure, one day per week would be devoted to explaining methodology and presenting a case study, with the second day focused on coaching. Given the case structure, the text does not contain homework problems. Instead, at the end of each chapter there are links to cases posted online.
商品描述(中文翻譯)
數學統計、統計圖形、計算機科學和運籌學的領域創造了現在所稱的分析方法(Analytics)。分析通常沿著三個極點進行特徵化:描述性分析(數據告訴我們什麼)、預測性分析(根據數據可以預測什麼,以及預測的確定性如何)和規範性分析(數據如何指導變更以改善系統性能)。本書專注於第二個極點,即預測性分析。預測數字、類別和動態行為的領域是不同的,使用的方法也各異。本書根據這些領域分為三個部分。預測數字的主題包括簡單和多重線性回歸、變數轉換、通過交叉驗證分析觀察數據、廣義線性模型、設計實驗,以及高斯過程和神經網絡回歸。分類方法包括神經網絡、邏輯回歸、k-最近鄰和線性判別分析。預測動態行為的方法包括趨勢分析、時間序列分析和離散事件動態模擬。特徵化預測不確定性是本書的關鍵重點。文本提供適合每個領域的分析方法,並明確說明如何應用這些方法。案例數據及相應的R代碼用於說明每種方法。《使用R的商業預測分析》旨在設計一種混合課程結構。課堂會議可以是講座形式和翻轉教室案例分析的結合。在每週兩次會議的十五週結構中,每週一天將專注於解釋方法論和呈現案例研究,第二天則專注於輔導。考慮到案例結構,文本中不包含家庭作業問題。相反,在每章結尾有指向在線發布的案例的鏈接。