Skip to content
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

Jump to bottom

[SPARK-7739][MLlib] Improve ChiSqSelector example code in user guide #7029

Closed
wants to merge 2 commits into from
Closed

[SPARK-7739][MLlib] Improve ChiSqSelector example code in user guide #7029

wants to merge 2 commits into from

Conversation

sethah
Copy link
Contributor

@sethah sethah commented Jun 26, 2015

No description provided.

mengxr
mengxr reviewed Jun 29, 2015
View reviewed changes
docs/mllib-feature-extraction.md
@@ -405,7 +405,7 @@ Note that the user can also construct a `ChiSqSelectorModel` by hand by providin

#### Example

The following example shows the basic use of ChiSqSelector.
The following example shows the basic use of ChiSqSelector. The data set used has a feature matrix consisting of greyscale values that vary from 0 - 255 for each feature.
Copy link
Contributor

Choose a reason for hiding this comment

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

0 - 255 -> 0 to 255

@mengxr
Copy link
Contributor

mengxr commented Jun 29, 2015

LGTM except minor style issues.

@mengxr
Copy link
Contributor

mengxr commented Jun 29, 2015

ok to test

@SparkQA
Copy link

SparkQA commented Jun 29, 2015

Test build #35960 has finished for PR 7029 at commit efea1f8.

  • This patch passes all tests.
  • This patch merges cleanly.
  • This patch adds the following public classes (experimental):
    • [ChiSqSelector](api/scala/index.html#org.apache.spark.mllib.feature.ChiSqSelector) stands for Chi-Squared feature selection. It operates on labeled data with categorical features.ChiSqSelectororders features based on a Chi-Squared test of independence from the class, and then filters (selects) the top features which the class label depends on the most. This is akin to yielding the features with the most predictive power.

@SparkQA
Copy link

SparkQA commented Jun 29, 2015

Test build #35996 has finished for PR 7029 at commit ef96916.

  • This patch passes all tests.
  • This patch merges cleanly.
  • This patch adds the following public classes (experimental):
    • [ChiSqSelector](api/scala/index.html#org.apache.spark.mllib.feature.ChiSqSelector) stands for Chi-Squared feature selection. It operates on labeled data with categorical features.ChiSqSelectororders features based on a Chi-Squared test of independence from the class, and then filters (selects) the top features which the class label depends on the most. This is akin to yielding the features with the most predictive power.

@AmplabJenkins
Copy link

Merged build finished. Test FAILed.

@jkbradley
Copy link
Member

LGTM merging into master
Thanks!

@asfgit asfgit closed this in 8d23587 Jun 30, 2015
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Reviewers
No reviews
Assignees
No one assigned
Labels
None yet
Projects
None yet
Milestone
No milestone
5 participants
@sethah @mengxr @SparkQA @AmplabJenkins @jkbradley