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Posted to commits@spark.apache.org by gu...@apache.org on 2020/03/02 01:34:00 UTC
[spark] branch master updated: [SPARK-30995][ML][DOCS] Latex
doesn't work correctly in FMClassifier/FMRegressor Scala doc
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gurwls223 pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/spark.git
The following commit(s) were added to refs/heads/master by this push:
new 0a5e9a1 [SPARK-30995][ML][DOCS] Latex doesn't work correctly in FMClassifier/FMRegressor Scala doc
0a5e9a1 is described below
commit 0a5e9a12a7d87ee1938368b971e4e18a3f8e84ef
Author: Huaxin Gao <hu...@us.ibm.com>
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 <hu...@us.ibm.com>
Signed-off-by: HyukjinKwon <gu...@apache.org>
---
.../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 87ae11b..4d85037 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
@@ -51,12 +51,16 @@ 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 6461faf..4cbc061 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
@@ -276,12 +276,16 @@ 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
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