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-rw-r--r--docs/mllib-linear-methods.md21
1 files changed, 11 insertions, 10 deletions
diff --git a/docs/mllib-linear-methods.md b/docs/mllib-linear-methods.md
index eff617d864..4dfbebbcd0 100644
--- a/docs/mllib-linear-methods.md
+++ b/docs/mllib-linear-methods.md
@@ -1,6 +1,7 @@
---
layout: global
-title: <a href="mllib-guide.html">MLlib</a> - Linear Methods
+title: Linear Methods - MLlib
+displayTitle: <a href="mllib-guide.html">MLlib</a> - Linear Methods
---
* Table of contents
@@ -233,7 +234,7 @@ val modelL1 = svmAlg.run(training)
{% endhighlight %}
Similarly, you can use replace `SVMWithSGD` by
-[`LogisticRegressionWithSGD`](api/mllib/index.html#org.apache.spark.mllib.classification.LogisticRegressionWithSGD).
+[`LogisticRegressionWithSGD`](api/scala/index.html#org.apache.spark.mllib.classification.LogisticRegressionWithSGD).
</div>
@@ -328,8 +329,8 @@ println("training Mean Squared Error = " + MSE)
{% endhighlight %}
Similarly you can use
-[`RidgeRegressionWithSGD`](api/mllib/index.html#org.apache.spark.mllib.regression.RidgeRegressionWithSGD)
-and [`LassoWithSGD`](api/mllib/index.html#org.apache.spark.mllib.regression.LassoWithSGD).
+[`RidgeRegressionWithSGD`](api/scala/index.html#org.apache.spark.mllib.regression.RidgeRegressionWithSGD)
+and [`LassoWithSGD`](api/scala/index.html#org.apache.spark.mllib.regression.LassoWithSGD).
</div>
@@ -380,11 +381,11 @@ all three possible regularizations (none, L1 or L2).
Algorithms are all implemented in Scala:
-* [SVMWithSGD](api/mllib/index.html#org.apache.spark.mllib.classification.SVMWithSGD)
-* [LogisticRegressionWithSGD](api/mllib/index.html#org.apache.spark.mllib.classification.LogisticRegressionWithSGD)
-* [LinearRegressionWithSGD](api/mllib/index.html#org.apache.spark.mllib.regression.LinearRegressionWithSGD)
-* [RidgeRegressionWithSGD](api/mllib/index.html#org.apache.spark.mllib.regression.RidgeRegressionWithSGD)
-* [LassoWithSGD](api/mllib/index.html#org.apache.spark.mllib.regression.LassoWithSGD)
+* [SVMWithSGD](api/scala/index.html#org.apache.spark.mllib.classification.SVMWithSGD)
+* [LogisticRegressionWithSGD](api/scala/index.html#org.apache.spark.mllib.classification.LogisticRegressionWithSGD)
+* [LinearRegressionWithSGD](api/scala/index.html#org.apache.spark.mllib.regression.LinearRegressionWithSGD)
+* [RidgeRegressionWithSGD](api/scala/index.html#org.apache.spark.mllib.regression.RidgeRegressionWithSGD)
+* [LassoWithSGD](api/scala/index.html#org.apache.spark.mllib.regression.LassoWithSGD)
Python calls the Scala implementation via
-[PythonMLLibAPI](api/mllib/index.html#org.apache.spark.mllib.api.python.PythonMLLibAPI).
+[PythonMLLibAPI](api/scala/index.html#org.apache.spark.mllib.api.python.PythonMLLibAPI).