Skip to content

L1-norm and L2-norm regularization doc #3586

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.

Sign up for GitHub

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

Merged
merged 12 commits into from
May 28, 2019
Merged

L1-norm and L2-norm regularization doc #3586

Changes from 1 commit
Commits
Show all changes
12 commits
Select commit Hold shift + click to select a range
1cb88a0
L1-norm and L2-norm regularization doc
wschin Apr 25, 2019
ad3d98e
Address comments
wschin Apr 25, 2019
a05da4a
Shared content
wschin Apr 25, 2019
31eaa2d
reuse content
wschin Apr 25, 2019
b7c88c6
Address comments
wschin Apr 25, 2019
4cca10d
Update docs/api-reference/regularization-l1-l2.md
natke Apr 26, 2019
5c95b53
Update docs/api-reference/regularization-l1-l2.md
natke Apr 26, 2019
8feae96
Update regularization-l1-l2.md
najeeb-kazmi Apr 26, 2019
bf948b6
Clear
wschin Apr 26, 2019
74e81ff
Merge branch 'l1l2' of github.com:wschin/machinelearning into l1l2
wschin Apr 26, 2019
2cb578a
Merge branch 'master' into l1l2
wschin May 24, 2019
0c7d9f9
Explain ER and loss
wschin May 24, 2019
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
Prev Previous commit
Explain ER and loss
  • Loading branch information
@wschin
wschin committed May 24, 2019
commit 0c7d9f9cfd21bf1447c29d652266f7526e086006
1 change: 1 addition & 0 deletions docs/api-reference/regularization-l1-l2.md
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,5 +1,6 @@
This class uses [empricial risk minimization](https://en.wikipedia.org/wiki/Empirical_risk_minimization) (i.e., ERM)
Copy link

@shmoradims shmoradims May 16, 2019 •
edited by wschin
Loading

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

This [](start = 0, length = 5)

Please add a header '### Regularization' so that the following text becomes a separate section. Also move it after all the algo details.
#ByDesign

Copy link
Member Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

No. I don't only mean regularization. It is a brief introduction to the whole optimization problem.

In reply to: 284914354 [](ancestors = 284914354)

to formulate the optimization problem built upon collected data.
Note that empricial risk is usually measured by applying a loss function on the model's predictions on collected data points.
If the training data does not contain enough data points
(for example, to train a linear model in $n$-dimensional space, we need at least $n$ data points),
[overfitting](https://en.wikipedia.org/wiki/Overfitting) may happen so that
Expand Down