Linear & Logistic regression

Can a cancer detection problem be solved by logistic regression?

• Sometimes

• yes

• no

• depends on the dataset

In logistic regression, the output is a probability. What function is used to map the input to a probability between 0 and 1?

• Linear function

• Softmax function

• Sigmoid function

• None of them

What does the logistic regression model estimate?

• The likelihood of a linear relationship between variables

• The probability that a given instance belongs to a particular class

• The residuals of the model

• The value of the dependent variable as a continuous number

Which of the following statements is true about the relationship between linear and logistic regression?

• Logistic regression is a generalized version of linear regression

• Both models are used to predict continuous values

• Logistic regression is preferred when predicting categorical outcomes

• Both models assume normally distributed errors

In regression analysis, the variable that is being predicted is

• the independent variable

• the dependent variable

• variable denoted by x

• variable denoted by y

The learner is trying to predict housing prices based on the size of each house. The variable 'size' is

• dependent variable

• label set variable

• independent variable

• target variable