Finally, you will see how you can score new data and export your predictions. Assessing a model’s performance is as important as building it this book will also show you how to do that. This book provides an overview of various popular data modeling techniques and presents a detailed case study of how to use CHAID, a decision tree model. The authors have drawn upon their decades of teaching thousands of new users, to choose those aspects of Modeler that you should learn first, so that you get off to a good start using proven best practices. Using a single case study throughout, this intentionally short and focused book sticks to the essentials. You will learn how to read data into Modeler, assess data quality, prepare your data for modeling, find interesting patterns and relationships within your data, and export your predictions. This book takes a detailed, step-by-step approach to introducing data mining using the de facto standard process, CRISP-DM, and Modeler’s easy to learn “visual programming” style. Since it is popular in corporate settings, widely available in university settings, and highly compatible with all the latest technologies, it is the perfect way to start your Data Science and Machine Learning journey. With almost 25 years of history, Modeler is the most established and comprehensive Data Mining workbench available. IBM SPSS Modeler allows users to quickly and efficiently use predictive analytics and gain insights from your data.

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