-
Notifications
You must be signed in to change notification settings - Fork 116
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Implementation of dropcollinear
feature in GeneralizedLinearModel
#488
Conversation
Adding PowerLink link function in GLM
Test was failing in Julia Nightly as: 1) GLM.linkinv(InverseLink(), 10) was 0.01 while GLM.linkinv(PowerLink(-1), 10) was 0.010000000000000002 2) GLM.linkinv(InverseSquareLink(), 10) was -10.01 while GLM.linkinv(PowerLink(-2), 10) was -0.010000000000000002 Rounding off to 2 digits should solve this. Note: These tests were passing in other versions of Julia.
…ed it for the docs
…(-2), 10 to 2 digits
Correcting order of PowerLink, ProbitLink, SqrtLink. Co-authored-by: Milan Bouchet-Valat <nalimilan@club.fr>
Using ≈ instead of isapprox. Co-authored-by: Milan Bouchet-Valat <nalimilan@club.fr>
Using alphabetical order in references. Co-authored-by: Milan Bouchet-Valat <nalimilan@club.fr>
Writing the example description in plain text. Co-authored-by: Milan Bouchet-Valat <nalimilan@club.fr>
Removing extra space to be consistent with the style. Co-authored-by: Milan Bouchet-Valat <nalimilan@club.fr>
Using a better variable name for 1 by lambda. Co-authored-by: Milan Bouchet-Valat <nalimilan@club.fr>
Using inline function. Co-authored-by: Milan Bouchet-Valat <nalimilan@club.fr>
Making the doctest code concise. Co-authored-by: Milan Bouchet-Valat <nalimilan@club.fr>
Removing the R code. Co-authored-by: Milan Bouchet-Valat <nalimilan@club.fr>
Removing test of hashes. Co-authored-by: Milan Bouchet-Valat <nalimilan@club.fr>
…few more metrics to test, also replaced all `=` by `≈` for real numbers
Since we are storing the link - the `GLM.Link` function can be defined uniformly for all link functions Co-authored-by: Milan Bouchet-Valat <nalimilan@club.fr>
Thanks @nalimilan |
Hi @nalimilan, We have updated the newly added We also added a test case to check the |
Maybe another example would pass tests more reliably? We really need to check that path. How about trying with categorical variables, like in the "rankdeficient" testset for linear models? |
Okay. Let me check. |
Added two test cases similar to |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Seems almost ready! Just a few stylistic comments.
Co-authored-by: Milan Bouchet-Valat <nalimilan@club.fr>
Co-authored-by: Milan Bouchet-Valat <nalimilan@club.fr>
Co-authored-by: Milan Bouchet-Valat <nalimilan@club.fr>
Co-authored-by: Milan Bouchet-Valat <nalimilan@club.fr>
Co-authored-by: Milan Bouchet-Valat <nalimilan@club.fr>
Co-authored-by: Milan Bouchet-Valat <nalimilan@club.fr>
Co-authored-by: Milan Bouchet-Valat <nalimilan@club.fr>
Co-authored-by: Milan Bouchet-Valat <nalimilan@club.fr>
Co-authored-by: Milan Bouchet-Valat <nalimilan@club.fr>
Co-authored-by: Bogumił Kamiński <bkamins@sgh.waw.pl>
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Thanks!
This pull request supersedes #340
We are looking for the
dropcollinear
feature in GLM and found #340. The PR, which opened in Oct'2019, looks very close to complete.Apart from the changes covered in PR 340, we have added
dof
forCholeskyPivoted
since thedof
will be calculated based on rank, instead of the number of coefficients.dropcollinear
in the list of keyword arguments.We have performed logistic regression with 10 independent variables, 10,000 rows and
dropcollinear
featuretrue
andfalse
; the dataset does not have a multicollinearity issue. The machine configuration is as follows: -OS – Linux,
CPU - AMD Ryzen 5 3600 6-Core Processor
RAM – 64 GB
With
dropcollinear
=true
: average time 4.381 msWith
dropcollinear
=false
: average time 4.396 ms