Lecture 5 Flashcards
1
Q
What is a necessary and sufficient condition for beta hat to be a solution of a Lasso regression?
A
2
Q
What is the Lasso is a piecewise linear for linear model theorem?
A
3
Q
What is shown in this graph? What does this imply?
A
4
Q
What is the idea of density estimation?
A
5
Q
What is the advantage of not making an assuption of the distribution? How can we then estimate the density?
A
6
Q
What is the effect of h in kernel density estimation?
A
7
Q
Why does Lambda have to be chosen for Lasso? (i.e. what problem does Lasso overcome, that introduces a new problem)
A
8
Q
What are the four steps of cross validation? What does this procedure create the best estimation for?
A
9
Q
A
