This course presents advanced models to predict categorical and continuous targets. Before reviewing the models, data preparation issues are addressed such as partitioning, detecting anomalies, and balancing data. The participant is first introduced to a technique named PCA/Factor, to reduce the number of fields to a number of core fields, referred to as components or factors. The next units focus on supervised models, including Decision List, Support Vector Machines, Random Trees, and XGBoost. Methods are reviewed to combine supervised models and execute them in a single run, both for categorical and continuous targets.
Course Length: 1 day(s)
Course Price: $835 CAD
Available Course Formats:
- Instructor Led Online
- Self-Paced Virtual Classroom
- Preparing data for modeling
- Address general data quality issues
- Handle anomalies
- Select important predictors
- Partition the data to better evaluate models
- Balance the data to build better models
- Reducing data with PCA/Factor
- Explain the idea behind PCA/Factor
- Determine the number of components/factors
- Explain the principle of rotating a solution
- Creating rulesets for flag targets with Decision List
- Explain how Decision List builds a ruleset
- Use Decision List interactively
- Create rulesets directly with Decision List
- Exploring advanced supervised models
- Explain the principles of Support Vector Machine (SVM)
- Explain the principles of Random Trees
- Explain the principles of XGBoost
- Combining models
- Use the Ensemble node to combine model predictions
- Improve model performance by meta-level modeling
- Finding the best supervised model
- Use the Auto Classifier node to find the best model for categorical targets
- Use the Auto Numeric node to find the best model for continuous targets
- Business Analysts
- Data Scientists
- Users of IBM SPSS Modeler responsible for building predictive models
- Familiarity with the IBM SPSS Modeler environment (creating, editing, opening, and saving streams).
- Familiarity with basic modeling techniques, either through completion of the courses Predictive Modeling for Categorical Targets Using IBM SPSS Modeler and/or Predictive Modeling for Continuous Targets Using IBM SPSS Modeler, or by experience with predictive models in IBM SPSS Modeler.
Instructor Led In Classroom
Newcomp can directly deliver IBM Business Analytics courses for Business Intelligence, Performance Management, and IBM Advanced Analytics through the use of in-class training facilities.
Currently, in-class courses are offered in Markham, Ottawa, Vancouver, Halifax, and Edmonton. Please note that classes can be added to new areas based on demand.
Instructor Led Online
Students receive the same quality as an in-class course, with a live instructor and the ability to participate in hands-on labs through real-life examples
ILOs help cut costs by reducing time and travel as they can be taken from home or the office and require only the use of a computer, high-speed wired internet and a headset.
Students can receive the same high-quality training, with the same courseware at their own speed and schedule with SPVC. Individuals with busy schedules can complete a course over a 30-day timeframe at a lower price than in-class or ILO courses. Please note that there is no live interaction with an instructor in this format.