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https://issues.apache.org/jira/browse/MAHOUT-2136?focusedWorklogId=539631&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-539631
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ASF GitHub Bot logged work on MAHOUT-2136:
------------------------------------------
Author: ASF GitHub Bot
Created on: 22/Jan/21 05:53
Start Date: 22/Jan/21 05:53
Worklog Time Spent: 10m
Work Description: josehernandezsc opened a new pull request #413:
URL: https://github.com/apache/mahout/pull/413
### Purpose of PR:
Mahout contribution: Implementation of Ridge Regression Algorithm by using
closed form method.
### Important ToDos
Please mark each with an "x"
- [X] A JIRA ticket exists (if not, please create this
first)[https://issues.apache.org/jira/browse/mahout/]
- [X] Title of PR is "MAHOUT-XXXX Brief Description of Changes" where XXXX
is the JIRA number.
- [X] Created unit tests where appropriate
- [X] Added licenses correct on newly added files
- [ ] Assigned JIRA to self
- [ ] Added documentation in scala docs/java docs, and to website
- [X] Successfully built and ran all unit tests, verified that all tests
pass locally.
If all of these things aren't complete, but you still feel it is
appropriate to open a PR, please add [WIP] after MAHOUT-XXXX before the
descriptions- e.g. "MAHOUT-XXXX [WIP] Description of Change"
Does this change break earlier versions?
No
Is this the beginning of a larger project for which a feature branch should
be made?
No
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Issue Time Tracking
-------------------
Worklog Id: (was: 539631)
Remaining Estimate: 335h 20m (was: 335.5h)
Time Spent: 40m (was: 0.5h)
> Implement Ridge Regression Algorithm
> ------------------------------------
>
> Key: MAHOUT-2136
> URL: https://issues.apache.org/jira/browse/MAHOUT-2136
> Project: Mahout
> Issue Type: Improvement
> Reporter: Jose Francisco Hernandez Santa Cruz
> Assignee: Jose Francisco Hernandez Santa Cruz
> Priority: Minor
> Original Estimate: 336h
> Time Spent: 40m
> Remaining Estimate: 335h 20m
>
> Ridge regression is a regularized approach of the linear regression by OLS
> method. Non-full rank matrices are allowed as the regularization parameter
> adds a diagonal matrix to the optimization equation breaking collinearity by
> adding a bias component, thus reducing standard error.
>
> https://en.wikipedia.org/wiki/Tikhonov_regularization
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