Advanced Predictive Modeling Using IBM SPSS Modeler (V16) SPVCIBM
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Häufig gestellte Fragen
You should have:
- Completion of the course Introduction to IBM SPSS Modeler and Data Mining (V16) or experience in analyzing data with IBM SPSS Modeler.
- Familiarity with basic modeling techniques, either through completion of the courses Classifying Customers Using IBM SPSS Modeler (V16) and Predicting Continuous Targets Using IBM SPSS Modeler (V16), or by experience with predictive models in IBM SPSS Modeler.
Was lernen Sie in diesem Kurs?
This course builds on the courses Classifying Customers Using IBM SPSS Modeler (V16) and Predicting Continuous Targets Using IBM SPSS Modeler (V16). It presents advanced techniques to predict categorical and continuous targets. Before reviewing the modeling techniques, data preparation issues are addressed such as partitioning and detecting anomalies. Also, a method to reduce the number of fields to a number of core fields, referred as components or factors, is presented. The next two modules focus on advanced predictive models, such as Decision List, Support Vector Machines and Bayes Net. Following this presentation, two modules present methods to combine individual models into a single model in order to improve predictive power, including running and evaluating many models in a single run, both for categorical and continuous targets.
If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course.
Training Paths that reference this course are:
- IBM SPSS Modeler – Analyst
Please refer to course overview for descriptio information.