000			02829nam a2200241 4500
005			20251015110958.0
008			251010b |||||||| |||| 00| 0 eng d
020			_a9783030830724
082			_a658.83 _bMCC
100			_aMcCarthy, Richard V _924907
245			_aApplying predictive analytics: _bfinding value in data
250			_a2nd
260			_aCham _bSpringer _c2022
300			_axv, 274 p.
365			_aINR _b5239.95
500			_aTable of contents: Front Matter Pages i-xv Download chapter PDF Introduction to Predictive Analytics Richard V. McCarthy, Mary M. McCarthy, Wendy Ceccucci Pages 1-26 Know Your Data: Data Preparation Richard V. McCarthy, Mary M. McCarthy, Wendy Ceccucci Pages 27-54 What Do Descriptive Statistics Tell Us Richard V. McCarthy, Mary M. McCarthy, Wendy Ceccucci Pages 55-85 Predictive Models Using Regression Richard V. McCarthy, Mary M. McCarthy, Wendy Ceccucci Pages 87-121 The Second of the Big 3: Decision Trees Richard V. McCarthy, Mary M. McCarthy, Wendy Ceccucci Pages 123-144 The Third of the Big 3: Neural Networks Richard V. McCarthy, Mary M. McCarthy, Wendy Ceccucci Pages 145-173 Model Comparisons and Scoring Richard V. McCarthy, Mary M. McCarthy, Wendy Ceccucci Pages 175-198 Finding Associations in Data Through Cluster Analysis Richard V. McCarthy, Mary M. McCarthy, Wendy Ceccucci Pages 199-232 Text Analytics: Using Qualitative Data to Support Quantitative Results Richard V. McCarthy, Mary M. McCarthy, Wendy Ceccucci Pages 233-254 [https://link.springer.com/book/10.1007/978-3-030-83070-0]
520			_aThe new edition of this textbook presents a practical, updated approach to predictive analytics for classroom learning. The authors focus on using analytics to solve business problems and compares several different modeling techniques, all explained from examples using the SAS Enterprise Miner software. The authors demystify complex algorithms to show how they can be utilized and explained within the context of enhancing business opportunities. Each chapter includes an opening vignette that provides real-life examples of how business analytics have been used in various aspects of organizations to solve issues or improve their results. A running case provides an example of a how to build and analyze a complex analytics model and utilize it to predict future outcomes. The new edition includes chapters on clusters and associations and text mining to support predictive models. An additional case is also included that can be used with each chapter or as a semester project. (https://link.springer.com/book/10.1007/978-3-030-83070-0)
650			_aMarketing analytics _915490
650			_aPredictive analytics _925594
700			_aMcCarthy, Mary M. _925447
700			_aCeccucci, Wendy _925448
942			_cBK _2ddc
999			_c10325 _d10325