Session 6 | U

What is the primary purpose of logistic regression?

• To predict continuous numerical values

• To classify data into categories

• To cluster data

• To reduce dimensionality

In logistic regression, the output is:

• A continuous value

• A probability value between 0 and 1

• Always an integer

• A categorical value

Which function is used in logistic regression to map predicted values to probabilities?

• Linear function

• Sigmoid function

• ReLU function

• Softmax function

What is the primary difference between linear regression and logistic regression?

• Linear regression predicts categorical outcomes; logistic regression predicts continuous values

• Logistic regression predicts categorical outcomes; linear regression predicts continuous values

• Both predict categorical outcomes

• Both predict continuous values

Which of the following is an activation function?

• Mean Squared Error

• Sigmoid

• Gradient Descent

• Cross-Entropy

What does the sigmoid function output when the input is a very large positive number?

• 0

• 1

• The same large positive number

• A negative number

Which loss function is commonly used in logistic regression?

• Mean Squared Error

• Hinge Loss

• Cross-Entropy Loss

• Log-Cosh Loss

What is the purpose of a loss function in machine learning?

• To transform input data

• To measure how well the model's predictions match the actual outcomes

• To normalize the data

• To split the data into training and testing sets

Which of the following is true about the output of the logistic regression model?

• It can be any real number

• It is a discrete class label directly

• It is a probability that can be thresholded to give a discrete class label

• It is always a binary value (0 or 1)

In the context of logistic regression, what does a decision boundary refer to?

• The line or hyperplane that separates the different classes

• The threshold value of the sigmoid function

• The slope of the regression line

• The value of the loss function