[SPARK-1434] [MLLIB] change labelParser from anonymous function to trait

This is a patch to address @mateiz 's comment in https://github.com/apache/spark/pull/245

MLUtils#loadLibSVMData uses an anonymous function for the label parser. Java users won't like it. So I make a trait for LabelParser and provide two implementations: binary and multiclass.

Author: Xiangrui Meng <meng@databricks.com>

Closes #345 from mengxr/label-parser and squashes the following commits:

ac44409 [Xiangrui Meng] use singleton objects for label parsers
3b1a7c6 [Xiangrui Meng] add tests for label parsers
c2e571c [Xiangrui Meng] rename LabelParser.apply to LabelParser.parse use extends for singleton
11c94e0 [Xiangrui Meng] add return types
7f8eb36 [Xiangrui Meng] change labelParser from annoymous function to trait
This commit is contained in:
Xiangrui Meng 2014-04-08 20:37:01 -07:00 committed by Patrick Wendell
parent ce8ec54561
commit b9e0c937df
4 changed files with 97 additions and 25 deletions

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@ -0,0 +1,49 @@
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.spark.mllib.util
/** Trait for label parsers. */
trait LabelParser extends Serializable {
/** Parses a string label into a double label. */
def parse(labelString: String): Double
}
/**
* Label parser for binary labels, which outputs 1.0 (positive) if the value is greater than 0.5,
* or 0.0 (negative) otherwise. So it works with +1/-1 labeling and +1/0 labeling.
*/
object BinaryLabelParser extends LabelParser {
/** Gets the default instance of BinaryLabelParser. */
def getInstance(): LabelParser = this
/**
* Parses the input label into positive (1.0) if the value is greater than 0.5,
* or negative (0.0) otherwise.
*/
override def parse(labelString: String): Double = if (labelString.toDouble > 0.5) 1.0 else 0.0
}
/**
* Label parser for multiclass labels, which converts the input label to double.
*/
object MulticlassLabelParser extends LabelParser {
/** Gets the default instance of MulticlassLabelParser. */
def getInstance(): LabelParser = this
override def parse(labelString: String): Double = labelString.toDouble
}

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@ -38,17 +38,6 @@ object MLUtils {
eps eps
} }
/**
* Multiclass label parser, which parses a string into double.
*/
val multiclassLabelParser: String => Double = _.toDouble
/**
* Binary label parser, which outputs 1.0 (positive) if the value is greater than 0.5,
* or 0.0 (negative) otherwise.
*/
val binaryLabelParser: String => Double = label => if (label.toDouble > 0.5) 1.0 else 0.0
/** /**
* Loads labeled data in the LIBSVM format into an RDD[LabeledPoint]. * Loads labeled data in the LIBSVM format into an RDD[LabeledPoint].
* The LIBSVM format is a text-based format used by LIBSVM and LIBLINEAR. * The LIBSVM format is a text-based format used by LIBSVM and LIBLINEAR.
@ -69,7 +58,7 @@ object MLUtils {
def loadLibSVMData( def loadLibSVMData(
sc: SparkContext, sc: SparkContext,
path: String, path: String,
labelParser: String => Double, labelParser: LabelParser,
numFeatures: Int, numFeatures: Int,
minSplits: Int): RDD[LabeledPoint] = { minSplits: Int): RDD[LabeledPoint] = {
val parsed = sc.textFile(path, minSplits) val parsed = sc.textFile(path, minSplits)
@ -89,7 +78,7 @@ object MLUtils {
}.reduce(math.max) }.reduce(math.max)
} }
parsed.map { items => parsed.map { items =>
val label = labelParser(items.head) val label = labelParser.parse(items.head)
val (indices, values) = items.tail.map { item => val (indices, values) = items.tail.map { item =>
val indexAndValue = item.split(':') val indexAndValue = item.split(':')
val index = indexAndValue(0).toInt - 1 val index = indexAndValue(0).toInt - 1
@ -107,14 +96,7 @@ object MLUtils {
* with number of features determined automatically and the default number of partitions. * with number of features determined automatically and the default number of partitions.
*/ */
def loadLibSVMData(sc: SparkContext, path: String): RDD[LabeledPoint] = def loadLibSVMData(sc: SparkContext, path: String): RDD[LabeledPoint] =
loadLibSVMData(sc, path, binaryLabelParser, -1, sc.defaultMinSplits) loadLibSVMData(sc, path, BinaryLabelParser, -1, sc.defaultMinSplits)
/**
* Loads binary labeled data in the LIBSVM format into an RDD[LabeledPoint],
* with number of features specified explicitly and the default number of partitions.
*/
def loadLibSVMData(sc: SparkContext, path: String, numFeatures: Int): RDD[LabeledPoint] =
loadLibSVMData(sc, path, binaryLabelParser, numFeatures, sc.defaultMinSplits)
/** /**
* Loads labeled data in the LIBSVM format into an RDD[LabeledPoint], * Loads labeled data in the LIBSVM format into an RDD[LabeledPoint],
@ -124,7 +106,7 @@ object MLUtils {
def loadLibSVMData( def loadLibSVMData(
sc: SparkContext, sc: SparkContext,
path: String, path: String,
labelParser: String => Double): RDD[LabeledPoint] = labelParser: LabelParser): RDD[LabeledPoint] =
loadLibSVMData(sc, path, labelParser, -1, sc.defaultMinSplits) loadLibSVMData(sc, path, labelParser, -1, sc.defaultMinSplits)
/** /**
@ -135,7 +117,7 @@ object MLUtils {
def loadLibSVMData( def loadLibSVMData(
sc: SparkContext, sc: SparkContext,
path: String, path: String,
labelParser: String => Double, labelParser: LabelParser,
numFeatures: Int): RDD[LabeledPoint] = numFeatures: Int): RDD[LabeledPoint] =
loadLibSVMData(sc, path, labelParser, numFeatures, sc.defaultMinSplits) loadLibSVMData(sc, path, labelParser, numFeatures, sc.defaultMinSplits)

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@ -0,0 +1,41 @@
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.spark.mllib.util
import org.scalatest.FunSuite
class LabelParsersSuite extends FunSuite {
test("binary label parser") {
for (parser <- Seq(BinaryLabelParser, BinaryLabelParser.getInstance())) {
assert(parser.parse("+1") === 1.0)
assert(parser.parse("1") === 1.0)
assert(parser.parse("0") === 0.0)
assert(parser.parse("-1") === 0.0)
}
}
test("multiclass label parser") {
for (parser <- Seq(MulticlassLabelParser, MulticlassLabelParser.getInstance())) {
assert(parser.parse("0") == 0.0)
assert(parser.parse("+1") === 1.0)
assert(parser.parse("1") === 1.0)
assert(parser.parse("2") === 2.0)
assert(parser.parse("3") === 3.0)
}
}
}

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@ -80,7 +80,7 @@ class MLUtilsSuite extends FunSuite with LocalSparkContext {
Files.write(lines, file, Charsets.US_ASCII) Files.write(lines, file, Charsets.US_ASCII)
val path = tempDir.toURI.toString val path = tempDir.toURI.toString
val pointsWithNumFeatures = MLUtils.loadLibSVMData(sc, path, 6).collect() val pointsWithNumFeatures = MLUtils.loadLibSVMData(sc, path, BinaryLabelParser, 6).collect()
val pointsWithoutNumFeatures = MLUtils.loadLibSVMData(sc, path).collect() val pointsWithoutNumFeatures = MLUtils.loadLibSVMData(sc, path).collect()
for (points <- Seq(pointsWithNumFeatures, pointsWithoutNumFeatures)) { for (points <- Seq(pointsWithNumFeatures, pointsWithoutNumFeatures)) {
@ -93,7 +93,7 @@ class MLUtilsSuite extends FunSuite with LocalSparkContext {
assert(points(2).features === Vectors.sparse(6, Seq((1, 4.0), (3, 5.0), (5, 6.0)))) assert(points(2).features === Vectors.sparse(6, Seq((1, 4.0), (3, 5.0), (5, 6.0))))
} }
val multiclassPoints = MLUtils.loadLibSVMData(sc, path, MLUtils.multiclassLabelParser).collect() val multiclassPoints = MLUtils.loadLibSVMData(sc, path, MulticlassLabelParser).collect()
assert(multiclassPoints.length === 3) assert(multiclassPoints.length === 3)
assert(multiclassPoints(0).label === 1.0) assert(multiclassPoints(0).label === 1.0)
assert(multiclassPoints(1).label === -1.0) assert(multiclassPoints(1).label === -1.0)