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.

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