Module 2 – Supervised Learning: Logistic Regression

Front

What is the dependent variable in binary logistic regression?

Back

The dependent variable is a binary/dummy variable coded as 0 (failure) or 1 (success).

Front

What does logistic regression estimate?

Back

Logistic regression estimates the probability of an event occurring based on a dataset of independent variables.

Front

What is the range of the target/dependent variable in logistic regression?

Back

The target/dependent variable is bounded between 0 and 1.

Front

What is the formula for the odds in logistic regression?

Back

Odds = π / (1 - π), where π is the probability of success.

Front

What is the significance of the sigmoid function in logistic regression?

Back

The sigmoid function has an S-shaped curve that ranges between 0 and 1 for different values of the linear predictor.

Front

What are the two forms of binary logistic regression?

Back

The two forms are the logit form and the probability form.

Front

What does the odds ratio (OR) compare?

Back

The odds ratio compares the odds of an event occurring in two different groups.

Front

What is Maximum Likelihood Estimation (MLE) in logistic regression?

Back

MLE is a method used to estimate the beta parameters of logistic regression by optimizing for the best fit of log odds.

Front

What is the cost function in logistic regression?

Back

The cost function is a nonlinear function that measures the difference between predicted and actual outcomes.

Front

How does the slope in logistic regression relate to odds?

Back

When X is increased by 1, the odds are multiplied by e^(β1), where β1 is the coefficient for X.