OMSA Midterm 2 Exam Questions and Answers 100% Solved
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Course
OMSA
Institution
OMSA
OMSA Midterm 2 Exam Questions and
Answers 100% Solved
Overfitting - Number of factors is too close to or larger than number of
data points -- fitting to both real effects and random effects. Comes from
including too many variables!
Ways to avoid overfitting - - Need number of factors to be sam...
lasso method - ✔✔adds constraint tau to std reg model. chooses
coefficients to min sum of squared errors.
right value of tau dependent on 2 things:
1) # of variables you want
2) quality of the model as you allow more variables
Correlation -- picks just one to have non-0 coefficient. other is left out.
elastic net - ✔✔constrain combination of abs value and coefficients and
their squares -- mix of ridge and lasso.
need to scale and pick right value of tau + lambda
ridge regression - ✔✔similar to elastic net, but without abs value term
(lasso portion).
adds quadratic term that shrinks coefficient values (pushing reg coeff to 0
or regularizes them). this adds bias but shrinks variance as cannot shrink to
0 as easily as quadratic term
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