|Course code||0A032||Skill level||Advanced|
|Duration||3.0 days||Delivery type||Instructor led
|Course type||Public or Private on-site|
|Public price||See Partner website|
This course demonstrates how to develop models to predict categorical and continuous outcomes, using such techniques as neural networks, decision trees, logistic regression, support vector machines, and Bayesian network models. Use of the binary classifier and numeric predictor nodes to automate model selection is included. Feature selection and detection of outliers are discussed. Expert options for each modeling node are reviewed in detail and advice is provided on when and how to use each model. You will also learn how to combine two or more models to improve prediction. Independent Study Only: Syllabus is provided for each week's study and materials are completed privately by each participant. 1 time per week students will meet on-line to review course exercises with a Live Instructor.
Training Paths that reference this course are:
This advanced course follows either 'Introduction to IBM SPSS Modeler and Data Mining' or Advanced Data Preparation with IBM SPSS Modeler is essential for anyone who wishes to become familiar with the full range of modeling techniques available in IBM SPSS Modeler to create predictive models.