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author | Zheng RuiFeng <ruifengz@foxmail.com> | 2016-11-17 13:40:16 +0000 |
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committer | Sean Owen <sowen@cloudera.com> | 2016-11-17 13:40:16 +0000 |
commit | cdaf4ce9fe58c4606be8aa2a5c3756d30545c850 (patch) | |
tree | ccd3b1b51b7c46f01a10c467d306614e685ba4e5 /mllib | |
parent | de77c67750dc868d75d6af173c3820b75a9fe4b7 (diff) | |
download | spark-cdaf4ce9fe58c4606be8aa2a5c3756d30545c850.tar.gz spark-cdaf4ce9fe58c4606be8aa2a5c3756d30545c850.tar.bz2 spark-cdaf4ce9fe58c4606be8aa2a5c3756d30545c850.zip |
[SPARK-18480][DOCS] Fix wrong links for ML guide docs
## What changes were proposed in this pull request?
1, There are two `[Graph.partitionBy]` in `graphx-programming-guide.md`, the first one had no effert.
2, `DataFrame`, `Transformer`, `Pipeline` and `Parameter` in `ml-pipeline.md` were linked to `ml-guide.html` by mistake.
3, `PythonMLLibAPI` in `mllib-linear-methods.md` was not accessable, because class `PythonMLLibAPI` is private.
4, Other link updates.
## How was this patch tested?
manual tests
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Closes #15912 from zhengruifeng/md_fix.
Diffstat (limited to 'mllib')
3 files changed, 9 insertions, 9 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/LSH.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/LSH.scala index 333a8c364a..eb117c40ee 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/feature/LSH.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/feature/LSH.scala @@ -40,7 +40,7 @@ private[ml] trait LSHParams extends HasInputCol with HasOutputCol { * @group param */ final val outputDim: IntParam = new IntParam(this, "outputDim", "output dimension, where" + - "increasing dimensionality lowers the false negative rate, and decreasing dimensionality" + + " increasing dimensionality lowers the false negative rate, and decreasing dimensionality" + " improves the running performance", ParamValidators.gt(0)) /** @group getParam */ diff --git a/mllib/src/main/scala/org/apache/spark/ml/tree/impl/GradientBoostedTrees.scala b/mllib/src/main/scala/org/apache/spark/ml/tree/impl/GradientBoostedTrees.scala index 7bef899a63..ede0a060ee 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/tree/impl/GradientBoostedTrees.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/tree/impl/GradientBoostedTrees.scala @@ -34,7 +34,7 @@ private[spark] object GradientBoostedTrees extends Logging { /** * Method to train a gradient boosting model - * @param input Training dataset: RDD of [[org.apache.spark.mllib.regression.LabeledPoint]]. + * @param input Training dataset: RDD of [[LabeledPoint]]. * @param seed Random seed. * @return tuple of ensemble models and weights: * (array of decision tree models, array of model weights) @@ -59,7 +59,7 @@ private[spark] object GradientBoostedTrees extends Logging { /** * Method to validate a gradient boosting model - * @param input Training dataset: RDD of [[org.apache.spark.mllib.regression.LabeledPoint]]. + * @param input Training dataset: RDD of [[LabeledPoint]]. * @param validationInput Validation dataset. * This dataset should be different from the training dataset, * but it should follow the same distribution. @@ -162,7 +162,7 @@ private[spark] object GradientBoostedTrees extends Logging { * Method to calculate error of the base learner for the gradient boosting calculation. * Note: This method is not used by the gradient boosting algorithm but is useful for debugging * purposes. - * @param data Training dataset: RDD of [[org.apache.spark.mllib.regression.LabeledPoint]]. + * @param data Training dataset: RDD of [[LabeledPoint]]. * @param trees Boosted Decision Tree models * @param treeWeights Learning rates at each boosting iteration. * @param loss evaluation metric. @@ -184,7 +184,7 @@ private[spark] object GradientBoostedTrees extends Logging { /** * Method to compute error or loss for every iteration of gradient boosting. * - * @param data RDD of [[org.apache.spark.mllib.regression.LabeledPoint]] + * @param data RDD of [[LabeledPoint]] * @param trees Boosted Decision Tree models * @param treeWeights Learning rates at each boosting iteration. * @param loss evaluation metric. diff --git a/mllib/src/main/scala/org/apache/spark/ml/tree/impl/RandomForest.scala b/mllib/src/main/scala/org/apache/spark/ml/tree/impl/RandomForest.scala index b504f411d2..8ae5ca3c84 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/tree/impl/RandomForest.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/tree/impl/RandomForest.scala @@ -82,7 +82,7 @@ private[spark] object RandomForest extends Logging { /** * Train a random forest. * - * @param input Training data: RDD of [[org.apache.spark.mllib.regression.LabeledPoint]] + * @param input Training data: RDD of [[LabeledPoint]] * @return an unweighted set of trees */ def run( @@ -343,7 +343,7 @@ private[spark] object RandomForest extends Logging { /** * Given a group of nodes, this finds the best split for each node. * - * @param input Training data: RDD of [[org.apache.spark.ml.tree.impl.TreePoint]] + * @param input Training data: RDD of [[TreePoint]] * @param metadata Learning and dataset metadata * @param topNodesForGroup For each tree in group, tree index -> root node. * Used for matching instances with nodes. @@ -854,10 +854,10 @@ private[spark] object RandomForest extends Logging { * and for multiclass classification with a high-arity feature, * there is one bin per category. * - * @param input Training data: RDD of [[org.apache.spark.mllib.regression.LabeledPoint]] + * @param input Training data: RDD of [[LabeledPoint]] * @param metadata Learning and dataset metadata * @param seed random seed - * @return Splits, an Array of [[org.apache.spark.mllib.tree.model.Split]] + * @return Splits, an Array of [[Split]] * of size (numFeatures, numSplits) */ protected[tree] def findSplits( |