3. Logistic And Linear Regression And Nerual Networks

Question 1

What is linear regression used for?

Answer 1

Linear regression is used to understand relationships between variables

Question 2

What is logistics regression used for?

Answer 2

Logistic regression is used for binary classification tasks

Question 3

What is neural networks used for?

Answer 3

Neural networks is used in the simple form of an ANN feedforward network as a powerful approach to both classification and regression

Question 4

What does linear regression do?

Answer 4

Linear regression helps model the relationship between a dependent variable (response) and one or more independent variables (predictors).

Question 5

What is the purpose of weights in linear regression?

Answer 5

The weights help determine how much information a certain attribute or feature tells about the predicted variable or feature

Question 6

What is w_0 in linear regression?

Answer 6

It is a bias term, constant value allowing the model to make predictions even when all x’s are zero

Question 7

What is the basis function in linear regression?

Answer 7

Basis function allow you to transform your input space to create more flexible models with a constant term

Question 8

What is the purpose of logistic regression?

Answer 8

Logistic regression is used for binary classification tasks, modeling the probability of the positive class (coded as 1) with transformation ensuring that predicted probabilities always are between 1 and 0

Question 9

What is the purpose of neural networks?

Answer 9

Feedforward neural network (ANN and forward pass) used for both classification and regression, considering weighted connected neurons through layers.