Regularized regression open-source extension procedure enhancements in SPSS Statistics

Abstract: The latest version of IBM SPSS Statistics introduces a host of new statistical procedures, usability improvements and improved open-source extension integration.

In this webcast, you’ll learn about three new Python-based regularized linear regression commands for handling models with highly correlated predictors, or even singularities resulting from problems with more predictors than cases. Key takeaways:

  • Learn about new commands introduced within SPSS Statistics 29 for regularized linear regression modeling, fitting models using ridge, LASSO, and elastic net estimation
  • See how models can be fitted using specific values of regularization parameters, produce trace plots of regression coefficients for specified sets of regularization parameters, and select values of regularization parameters using cross-validation.
  • Simplify specification of analyses using command syntax or via graphical interfaces, so that analyses and output work as they do for native procedures




    #DataandAILearning
    #AIandDSSkills
    Event Image
    When:  Oct 19, 2022 from 12:00 PM to 02:00 PM (ET)

    Where

    Online Instructions:
    Url: http://ibm.biz/IBMSPSS_19thOct
    Login: https://ibm.biz/IBMSPSS_19thOct

    Contact

    Surekha Parekh

    surekha@uk.ibm.com