concepts, techniques, and applications with XLMiner® Shmueli, Galit creator autor. aut Bruce, Peter C. Patel, Nitin R. text nju 2016 3. monographic spa eng

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514 páginas : : figuras ; tables. Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner®, Third Edition is an ideal textbook for upper-undergraduate and graduate-level courses as well as professional programs on data mining, predictive modeling, and Big Data analytics. The new edition is also a unique reference for analysts, researchers, and practitioners working with predictive analytics in the fields of business, finance, marketing, computer science, and information technology. CHAPTER 1 Introduction -- CHAPTER 2 Overview of the Data Mining Process. -- CHAPTER 3 Data Visualization. -- CHAPTER 4 Dimension Reduction. -- CHAPTER 5 Evaluating Predictive Performance. -- CHAPTER 6 Multiple Linear Regression. -- CHAPTER 7 k-Nearest Neighbors (kNN). -- CHAPTER 8 The Naive Bayes Classifier. -- CHAPTER 9 Classification and Regression Trees. -- CHAPTER 10 Logistic Regression. -- CHAPTER 11 Neural Nets. -- CHAPTER 12 Discriminant Analysis. -- CHAPTER 13 Combining Methods: Ensembles and Uplift Modeling. -- CHAPTER 14 Association Rules and Collaborative Filtering. -- CHAPTER 15 Cluster Analysis. -- CHAPTER 16 Handling Time Series. -- CHAPTER 17 Regression-Based Forecasting. -- CHAPTER 18 Smoothing Methods. -- CHAPTER 19 Social Network Analytics. -- CHAPTER 20 Text Mining. -- CHAPTER 21 Cases. Contents. Hojas de cálculo electrónicas Electronic spreadsheets Hojas de cálculo programas informáticos Spreadsheets Computer programs Hojas de cálculo software informático Spreadsheets Computer software 005.54 S558 9781118729274 CO-ViULL 230503 20251030135902.0 spa