This is an automated email from the ASF dual-hosted git repository.
gurwls223 pushed a commit to branch branch-3.0
in repository https://gitbox.apache.org/repos/asf/spark.git
The following commit(s) were added to refs/heads/branch-3.0 by this push:
new 88d4be2 [SPARK-30995][ML][DOCS] Latex doesn't work correctly in
FMClassifier/FMRegressor Scala doc
88d4be2 is described below
commit 88d4be2c0b92bf719f77ea7063e969fe58a6d604
Author: Huaxin Gao <[email protected]>
AuthorDate: Mon Mar 2 10:33:26 2020 +0900
[SPARK-30995][ML][DOCS] Latex doesn't work correctly in
FMClassifier/FMRegressor Scala doc
### What changes were proposed in this pull request?
Latex doesn't work correctly
### Why are the changes needed?
Fix the doc to make Latex work
### Does this PR introduce any user-facing change?
Before fix:
After fix:
### How was this patch tested?
Manually build doc and test
Closes #27748 from huaxingao/fm_doc.
Authored-by: Huaxin Gao <[email protected]>
Signed-off-by: HyukjinKwon <[email protected]>
(cherry picked from commit 0a5e9a12a7d87ee1938368b971e4e18a3f8e84ef)
Signed-off-by: HyukjinKwon <[email protected]>
---
.../org/apache/spark/ml/classification/FMClassifier.scala | 10 +++++++---
.../scala/org/apache/spark/ml/regression/FMRegressor.scala | 10 +++++++---
2 files changed, 14 insertions(+), 6 deletions(-)
diff --git
a/mllib/src/main/scala/org/apache/spark/ml/classification/FMClassifier.scala
b/mllib/src/main/scala/org/apache/spark/ml/classification/FMClassifier.scala
index d511c1b..3057d51 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/FMClassifier.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/FMClassifier.scala
@@ -52,12 +52,16 @@ private[classification] trait FMClassifierParams extends
ProbabilisticClassifier
* FM is able to estimate interactions even in problems with huge sparsity
* (like advertising and recommendation system).
* FM formula is:
- * {{{
+ * <blockquote>
+ * $$
+ * \begin{align}
* y = \sigma\left( w_0 + \sum\limits^n_{i-1} w_i x_i +
* \sum\limits^n_{i=1} \sum\limits^n_{j=i+1} \langle v_i, v_j \rangle x_i
x_j \right)
- * }}}
+ * \end{align}
+ * $$
+ * </blockquote>
* First two terms denote global bias and linear term (as same as linear
regression),
- * and last term denotes pairwise interactions term. {{{v_i}}} describes the
i-th variable
+ * and last term denotes pairwise interactions term. v_i describes the i-th
variable
* with k factors.
*
* FM classification model uses logistic loss which can be solved by gradient
descent method, and
diff --git
a/mllib/src/main/scala/org/apache/spark/ml/regression/FMRegressor.scala
b/mllib/src/main/scala/org/apache/spark/ml/regression/FMRegressor.scala
index f7810eb..a612448 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/regression/FMRegressor.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/regression/FMRegressor.scala
@@ -277,12 +277,16 @@ private[regression] trait FMRegressorParams extends
FactorizationMachinesParams
* FM is able to estimate interactions even in problems with huge sparsity
* (like advertising and recommendation system).
* FM formula is:
- * {{{
+ * <blockquote>
+ * $$
+ * \begin{align}
* y = w_0 + \sum\limits^n_{i-1} w_i x_i +
* \sum\limits^n_{i=1} \sum\limits^n_{j=i+1} \langle v_i, v_j \rangle x_i
x_j
- * }}}
+ * \end{align}
+ * $$
+ * </blockquote>
* First two terms denote global bias and linear term (as same as linear
regression),
- * and last term denotes pairwise interactions term. {{{v_i}}} describes the
i-th variable
+ * and last term denotes pairwise interactions term. v_i describes the i-th
variable
* with k factors.
*
* FM regression model uses MSE loss which can be solved by gradient descent
method, and
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
