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Posted to commits@spark.apache.org by me...@apache.org on 2014/12/04 13:17:28 UTC
spark git commit: [FIX][DOC] Fix broken links in ml-guide.md
Repository: spark
Updated Branches:
refs/heads/master 469a6e5f3 -> 7e758d709
[FIX][DOC] Fix broken links in ml-guide.md
and some minor changes in ScalaDoc.
Author: Xiangrui Meng <me...@databricks.com>
Closes #3601 from mengxr/SPARK-4575-fix and squashes the following commits:
c559768 [Xiangrui Meng] minor code update
ce94da8 [Xiangrui Meng] Java Bean -> JavaBean
0b5c182 [Xiangrui Meng] fix links in ml-guide
Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/7e758d70
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/7e758d70
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/7e758d70
Branch: refs/heads/master
Commit: 7e758d709286e73d2c878d4a2d2b4606386142c7
Parents: 469a6e5
Author: Xiangrui Meng <me...@databricks.com>
Authored: Thu Dec 4 20:16:35 2014 +0800
Committer: Xiangrui Meng <me...@databricks.com>
Committed: Thu Dec 4 20:16:35 2014 +0800
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docs/ml-guide.md | 8 ++++----
.../apache/spark/examples/ml/JavaCrossValidatorExample.java | 1 -
.../apache/spark/examples/ml/JavaSimpleParamsExample.java | 2 +-
mllib/src/main/scala/org/apache/spark/ml/param/params.scala | 1 -
4 files changed, 5 insertions(+), 7 deletions(-)
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http://git-wip-us.apache.org/repos/asf/spark/blob/7e758d70/docs/ml-guide.md
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diff --git a/docs/ml-guide.md b/docs/ml-guide.md
index 012fbd9..1c2e273 100644
--- a/docs/ml-guide.md
+++ b/docs/ml-guide.md
@@ -31,7 +31,7 @@ E.g., a learning algorithm is an `Estimator` which trains on a dataset and produ
* **[`Pipeline`](ml-guide.html#pipeline)**: A `Pipeline` chains multiple `Transformer`s and `Estimator`s together to specify an ML workflow.
-* **[`Param`](ml-guide.html#param)**: All `Transformer`s and `Estimator`s now share a common API for specifying parameters.
+* **[`Param`](ml-guide.html#parameters)**: All `Transformer`s and `Estimator`s now share a common API for specifying parameters.
## ML Dataset
@@ -134,7 +134,7 @@ Each stage's `transform()` method updates the dataset and passes it to the next
Spark ML `Estimator`s and `Transformer`s use a uniform API for specifying parameters.
A [`Param`](api/scala/index.html#org.apache.spark.ml.param.Param) is a named parameter with self-contained documentation.
-A [`ParamMap`](api/scala/index.html#org.apache.spark.ml.param.ParamMap)] is a set of (parameter, value) pairs.
+A [`ParamMap`](api/scala/index.html#org.apache.spark.ml.param.ParamMap) is a set of (parameter, value) pairs.
There are two main ways to pass parameters to an algorithm:
@@ -148,7 +148,7 @@ This is useful if there are two algorithms with the `maxIter` parameter in a `Pi
# Code Examples
This section gives code examples illustrating the functionality discussed above.
-There is not yet documentation for specific algorithms in Spark ML. For more info, please refer to the [API Documentation](api/scala/index.html). Spark ML algorithms are currently wrappers for MLlib algorithms, and the [MLlib programming guide](mllib-guide.html) has details on specific algorithms.
+There is not yet documentation for specific algorithms in Spark ML. For more info, please refer to the [API Documentation](api/scala/index.html#org.apache.spark.ml.package). Spark ML algorithms are currently wrappers for MLlib algorithms, and the [MLlib programming guide](mllib-guide.html) has details on specific algorithms.
## Example: Estimator, Transformer, and Param
@@ -492,7 +492,7 @@ The `ParamMap` which produces the best evaluation metric (averaged over the `$k$
`CrossValidator` finally fits the `Estimator` using the best `ParamMap` and the entire dataset.
The following example demonstrates using `CrossValidator` to select from a grid of parameters.
-To help construct the parameter grid, we use the [`ParamGridBuilder`](api/scala/index.html#org.apache.spark.ml.tuning.ParamGridGuilder) utility.
+To help construct the parameter grid, we use the [`ParamGridBuilder`](api/scala/index.html#org.apache.spark.ml.tuning.ParamGridBuilder) utility.
Note that cross-validation over a grid of parameters is expensive.
E.g., in the example below, the parameter grid has 3 values for `hashingTF.numFeatures` and 2 values for `lr.regParam`, and `CrossValidator` uses 2 folds. This multiplies out to `$(3 \times 2) \times 2 = 12$` different models being trained.
http://git-wip-us.apache.org/repos/asf/spark/blob/7e758d70/examples/src/main/java/org/apache/spark/examples/ml/JavaCrossValidatorExample.java
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diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaCrossValidatorExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaCrossValidatorExample.java
index 3b156fa..f4b4f8d 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaCrossValidatorExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaCrossValidatorExample.java
@@ -23,7 +23,6 @@ import com.google.common.collect.Lists;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaSparkContext;
-import org.apache.spark.ml.Model;
import org.apache.spark.ml.Pipeline;
import org.apache.spark.ml.PipelineStage;
import org.apache.spark.ml.classification.LogisticRegression;
http://git-wip-us.apache.org/repos/asf/spark/blob/7e758d70/examples/src/main/java/org/apache/spark/examples/ml/JavaSimpleParamsExample.java
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diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaSimpleParamsExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaSimpleParamsExample.java
index cf58f4d..e25b271 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaSimpleParamsExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaSimpleParamsExample.java
@@ -47,7 +47,7 @@ public class JavaSimpleParamsExample {
JavaSQLContext jsql = new JavaSQLContext(jsc);
// Prepare training data.
- // We use LabeledPoint, which is a case class. Spark SQL can convert RDDs of Java Beans
+ // We use LabeledPoint, which is a JavaBean. Spark SQL can convert RDDs of JavaBeans
// into SchemaRDDs, where it uses the bean metadata to infer the schema.
List<LabeledPoint> localTraining = Lists.newArrayList(
new LabeledPoint(1.0, Vectors.dense(0.0, 1.1, 0.1)),
http://git-wip-us.apache.org/repos/asf/spark/blob/7e758d70/mllib/src/main/scala/org/apache/spark/ml/param/params.scala
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diff --git a/mllib/src/main/scala/org/apache/spark/ml/param/params.scala b/mllib/src/main/scala/org/apache/spark/ml/param/params.scala
index 4b4340a..04f9cfb 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/param/params.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/param/params.scala
@@ -220,7 +220,6 @@ class ParamMap private[ml] (private val map: mutable.Map[Param[Any], Any]) exten
/**
* Puts a list of param pairs (overwrites if the input params exists).
- * Not usable from Java
*/
@varargs
def put(paramPairs: ParamPair[_]*): this.type = {
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