Week 6- Friday

Logistic regression (classification) – text chapter 4

After watching the video, we have discussed the following terminologies in the class.

1. Review of Logistic Regression Concepts:
   • Recap of fundamental concepts in logistic regression, a statistical technique used for predicting binary outcomes. It involves understanding the logistic function, odds ratio, decision boundaries, and the process of maximum likelihood estimation.
2. Coefficients for Continuous Variables:
   • Numeric values assigned to continuous variables in logistic regression. These coefficients represent the change in log-odds for the outcome variable associated with a one-unit change in the continuous predictor.
3. Coefficients for Discrete Variables:
   • Weights assigned to dummy variables that represent discrete categories in logistic regression. These coefficients indicate how much the log-odds of
     the outcome change compared to a chosen reference category.
4. Coefficients for Combinations of Variable Types:
   • Weights associated with logistic regression models that include a mix of continuous and discrete variables. These coefficients demonstrate the joint influence of different types of variables on the log-odds of the predicted outcome.