Machine Learning Regression 5

Question 1

In Bayesian linear regression, what replaces the single point estimate of coefficients?

Accepted Answer

A posterior probability distribution over coefficients

Answer

Bayesian regression represents uncertainty by computing a posterior distribution over coefficients, combining prior beliefs with observed data.

Question 2

What does Cook's Distance measure in regression diagnostics?

Accepted Answer

The influence of removing an observation on all fitted values

Answer

Cook's Distance quantifies how much all predicted values change if a particular observation is removed, identifying influential data points.

Question 3

Which transformation is commonly applied to the response variable to address right-skewed data in regression?

Accepted Answer

Square root or log transformation

Answer

Log or square root transformations can stabilize variance and normalize right-skewed response distributions for regression analysis.

Question 4

In principal component regression (PCR), what is regressed on the response variable?

Accepted Answer

Principal components derived from predictors

Answer

PCR uses uncorrelated principal components of the predictors as inputs, addressing multicollinearity by projecting into a lower-dimensional space.

Question 5

What is the 'bias-variance tradeoff' in the context of regression models?

Accepted Answer

Balancing underfitting (high bias) against overfitting (high variance)

Answer

The bias-variance tradeoff describes how increasing model complexity reduces bias but increases variance, requiring a balance for optimal generalization.

Machine Learning Practice Test

Machine Learning Practice Test

Machine Learning Regression 5