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author | Tommy YU <tummyyu@163.com> | 2016-01-18 13:46:14 +0000 |
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committer | Sean Owen <sowen@cloudera.com> | 2016-01-18 13:46:14 +0000 |
commit | 233d6cee96bb4c1723a5ab36efd19fd6180d651c (patch) | |
tree | 3d98caea014a74a69daecb383d0c9d020742f97d /mllib | |
parent | bc36b0f1a1f38060700903be7bf5cf012b414551 (diff) | |
download | spark-233d6cee96bb4c1723a5ab36efd19fd6180d651c.tar.gz spark-233d6cee96bb4c1723a5ab36efd19fd6180d651c.tar.bz2 spark-233d6cee96bb4c1723a5ab36efd19fd6180d651c.zip |
[SPARK-10264][DOCUMENTATION] Added @Since to ml.recomendation
I create new pr since original pr long time no update.
Please help to review.
srowen
Author: Tommy YU <tummyyu@163.com>
Closes #10756 from Wenpei/add_since_to_recomm.
Diffstat (limited to 'mllib')
-rw-r--r-- | mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala | 33 |
1 files changed, 30 insertions, 3 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala b/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala index 472c1854d3..1481c8268a 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala @@ -180,22 +180,27 @@ private[recommendation] trait ALSParams extends ALSModelParams with HasMaxIter w * @param itemFactors a DataFrame that stores item factors in two columns: `id` and `features` */ @Experimental +@Since("1.3.0") class ALSModel private[ml] ( - override val uid: String, - val rank: Int, + @Since("1.4.0") override val uid: String, + @Since("1.4.0") val rank: Int, @transient val userFactors: DataFrame, @transient val itemFactors: DataFrame) extends Model[ALSModel] with ALSModelParams with MLWritable { /** @group setParam */ + @Since("1.4.0") def setUserCol(value: String): this.type = set(userCol, value) /** @group setParam */ + @Since("1.4.0") def setItemCol(value: String): this.type = set(itemCol, value) /** @group setParam */ + @Since("1.3.0") def setPredictionCol(value: String): this.type = set(predictionCol, value) + @Since("1.3.0") override def transform(dataset: DataFrame): DataFrame = { // Register a UDF for DataFrame, and then // create a new column named map(predictionCol) by running the predict UDF. @@ -213,6 +218,7 @@ class ALSModel private[ml] ( predict(userFactors("features"), itemFactors("features")).as($(predictionCol))) } + @Since("1.3.0") override def transformSchema(schema: StructType): StructType = { validateParams() SchemaUtils.checkColumnType(schema, $(userCol), IntegerType) @@ -220,6 +226,7 @@ class ALSModel private[ml] ( SchemaUtils.appendColumn(schema, $(predictionCol), FloatType) } + @Since("1.5.0") override def copy(extra: ParamMap): ALSModel = { val copied = new ALSModel(uid, rank, userFactors, itemFactors) copyValues(copied, extra).setParent(parent) @@ -303,65 +310,83 @@ object ALSModel extends MLReadable[ALSModel] { * preferences rather than explicit ratings given to items. */ @Experimental -class ALS(override val uid: String) extends Estimator[ALSModel] with ALSParams +@Since("1.3.0") +class ALS(@Since("1.4.0") override val uid: String) extends Estimator[ALSModel] with ALSParams with DefaultParamsWritable { import org.apache.spark.ml.recommendation.ALS.Rating + @Since("1.4.0") def this() = this(Identifiable.randomUID("als")) /** @group setParam */ + @Since("1.3.0") def setRank(value: Int): this.type = set(rank, value) /** @group setParam */ + @Since("1.3.0") def setNumUserBlocks(value: Int): this.type = set(numUserBlocks, value) /** @group setParam */ + @Since("1.3.0") def setNumItemBlocks(value: Int): this.type = set(numItemBlocks, value) /** @group setParam */ + @Since("1.3.0") def setImplicitPrefs(value: Boolean): this.type = set(implicitPrefs, value) /** @group setParam */ + @Since("1.3.0") def setAlpha(value: Double): this.type = set(alpha, value) /** @group setParam */ + @Since("1.3.0") def setUserCol(value: String): this.type = set(userCol, value) /** @group setParam */ + @Since("1.3.0") def setItemCol(value: String): this.type = set(itemCol, value) /** @group setParam */ + @Since("1.3.0") def setRatingCol(value: String): this.type = set(ratingCol, value) /** @group setParam */ + @Since("1.3.0") def setPredictionCol(value: String): this.type = set(predictionCol, value) /** @group setParam */ + @Since("1.3.0") def setMaxIter(value: Int): this.type = set(maxIter, value) /** @group setParam */ + @Since("1.3.0") def setRegParam(value: Double): this.type = set(regParam, value) /** @group setParam */ + @Since("1.3.0") def setNonnegative(value: Boolean): this.type = set(nonnegative, value) /** @group setParam */ + @Since("1.4.0") def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value) /** @group setParam */ + @Since("1.3.0") def setSeed(value: Long): this.type = set(seed, value) /** * Sets both numUserBlocks and numItemBlocks to the specific value. * @group setParam */ + @Since("1.3.0") def setNumBlocks(value: Int): this.type = { setNumUserBlocks(value) setNumItemBlocks(value) this } + @Since("1.3.0") override def fit(dataset: DataFrame): ALSModel = { import dataset.sqlContext.implicits._ val r = if ($(ratingCol) != "") col($(ratingCol)).cast(FloatType) else lit(1.0f) @@ -381,10 +406,12 @@ class ALS(override val uid: String) extends Estimator[ALSModel] with ALSParams copyValues(model) } + @Since("1.3.0") override def transformSchema(schema: StructType): StructType = { validateAndTransformSchema(schema) } + @Since("1.5.0") override def copy(extra: ParamMap): ALS = defaultCopy(extra) } |