Skip to content

[MINOR][DOC] Fix ml-guide markdown typos #20889

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

Closed
chucheng92 wants to merge 2 commits into from
Closed

[MINOR][DOC] Fix ml-guide markdown typos #20889

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
be9cadb
[MINOR][DOC] Fix ml-guide markdown typos
Mar 23, 2018
98cd710
[MINOR][DOC] Fix a few docs/mlib typos
Mar 23, 2018
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
2 changes: 1 addition & 1 deletion docs/ml-guide.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -111,7 +111,7 @@ and the migration guide below will explain all changes between releases.
* The class and trait hierarchy for logistic regression model summaries was changed to be cleaner
and better accommodate the addition of the multi-class summary. This is a breaking change for user
code that casts a `LogisticRegressionTrainingSummary` to a
` BinaryLogisticRegressionTrainingSummary`. Users should instead use the `model.binarySummary`
`BinaryLogisticRegressionTrainingSummary`. Users should instead use the `model.binarySummary`
method. See [SPARK-17139](https://issues.apache.org/jira/browse/SPARK-17139) for more detail
(_note_ this is an `Experimental` API). This _does not_ affect the Python `summary` method, which
will still work correctly for both multinomial and binary cases.
Expand Down
4 changes: 1 addition & 3 deletions docs/mllib-feature-extraction.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -277,9 +277,7 @@ for details on the API.
`ElementwiseProduct` multiplies each input vector by a provided "weight" vector, using element-wise
multiplication. In other words, it scales each column of the dataset by a scalar multiplier. This
represents the [Hadamard product](https://en.wikipedia.org/wiki/Hadamard_product_%28matrices%29)
between the input vector, `v` and transforming vector, `scalingVec`, to yield a result vector.
Qu8T948*1#
Denoting the `scalingVec` as "`w`," this transformation may be written as:
between the input vector, `v` and transforming vector, `scalingVec`, to yield a result vector. Denoting the `scalingVec` as "`w`", this transformation may be written as:

`\[ \begin{pmatrix}
v_1 \\
Expand Down