Model Selection for Optimal Prediction in Statistical Learning - Part 2 / 2

Time: Wednesday 27-May-2020 16:00

Live in 1 day & 21:30:44

Discussion Facilitator:


    Motivation / Abstract
    Professor Ernest will walk us through a statistical framework for model selection. His emphasis on investigating underlying probabilistic phenomenon is crucial to a methodical understanding of how the data behaves. This consistency will be shown through every step of the modelling journey; choosing the most appropriate metric for model accuracy and likelihood function, aggregation techniques, and how to evaluate model performance from a probabilistic and statistical perspective.
    Questions Discussed
    - Choosing appropriate metrics for model accuracy
    - Choosing appropriate likelihood functions
    - Aggregation techniques
    - Model performance evaluation
    ... But from a probabilistic perspective
    Stream Categories:
     SpotlightAuthor SpeakingML Interpretability