Seminar #51 - Machine Learning - How Variable Importance Works

In Exploratory, when you build machine learning or statistical learning models you will see a tab called 'Importance' that shows which variables are more important to predict a given target variable values.

In this seminar, Kan discussed how the variable importance was calculated as well as how to interpret the result. Also, he introduced a method called 'Boruta', which is used address challenges brought by the randomness of the Random Forest models.

Agenda:

• Prediction Model
• Analytics Grammar
• Variable Importance
• Statistical Learning - Variable Importance vs. Coefficient
• Statistical Learning - Significance of Relationship
• Random Forest - Boruta for Variable Importance

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For the upcoming seminars, check out our Exploratory Online Seminar page!