Define logistic regression.
A statistical method for predicting binary classes using a logistic function.
True or false: Logistic regression can only handle binary outcomes.
FALSE
Logistic regression can be extended to handle multiple classes using multinomial logistic regression.
What is the logit function?
The natural logarithm of the odds of the probability of an event occurring.
Fill in the blank: The output of logistic regression is a _______ value.
probability
What does the sigmoid function do in logistic regression?
It maps any real-valued number into the range between 0 and 1.
Define odds.
The ratio of the probability of an event occurring to the probability of it not occurring.
What is the purpose of the cost function in logistic regression?
To measure how well the model’s predictions match the actual outcomes.
True or false: Logistic regression assumes a linear relationship between the independent and dependent variables.
TRUE
What is maximum likelihood estimation?
A method for estimating the parameters of a statistical model that maximizes the likelihood function.
Fill in the blank: In logistic regression, the coefficients represent the change in the log odds of the outcome for a _______.
one-unit change in the predictor
Define multicollinearity.
A situation where two or more predictors are highly correlated, affecting the model’s estimates.
What is the confusion matrix?
A table used to evaluate the performance of a classification model by comparing predicted and actual values.
True or false: Logistic regression can provide probabilities for class membership.
TRUE
What does the area under the ROC curve (AUC) represent?
The ability of a model to distinguish between classes; higher values indicate better performance.
Fill in the blank: The threshold in logistic regression determines the cutoff for classifying an instance as _______.
positive
What is the interpretation of the odds ratio in logistic regression?
It indicates how much the odds of the outcome change with a one-unit increase in the predictor.
Define regularization.
A technique used to prevent overfitting by adding a penalty to the loss function.
What is L1 regularization also known as?
Lasso regression
True or false: Logistic regression can handle non-linear relationships without transformation.
FALSE
Non-linear relationships often require transformations or polynomial terms.
What is the link function in logistic regression?
A function that connects the linear predictor to the mean of the distribution function.
Fill in the blank: In logistic regression, the dependent variable is _______.
binary
What is the main assumption of logistic regression regarding the errors?
The errors are assumed to be independent and follow a binomial distribution.
Define pseudo R-squared.
A measure that provides an indication of the goodness of fit for logistic regression models.
What is the Hosmer-Lemeshow test used for?
To assess the goodness of fit of a logistic regression model.
