Webinars
Feature Selection in IBM SPSS Statistics
Feature selection is a crucial step in data preprocessing, helping you identify the most important input variables that drive your outcomes. In this session, you’ll discover how effective feature selection can:
- Boost model accuracy by reducing overfitting
- Accelerate training by working with fewer, more relevant features
- Simplify model design for easier interpretation and deployment
- Reduce data noise by eliminating irrelevant information
- Enable comprehensive testing of relationships in a single analysis, rather than multiple tests
What will you learn?
- What is Feature Selection?
- What is Predictor Selection?
- What is Boruta Feature Selection?
- Practical tips for running these procedures and interpreting the results in IBM SPSS Statistics
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Webinars