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[SPARK-13338][ML] Allow setting 'degree' parameter to 1 for PolynomialExpansion

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Author: Grzegorz Chilkiewicz <grzegorz.chilkiewicz@codilime.com>

Closes #11216 from grzegorz-chilkiewicz/master.
This commit is contained in:
Grzegorz Chilkiewicz 2016-02-23 10:30:02 -08:00 committed by Xiangrui Meng
parent 4d1e5f92e1
commit 5d69eaf097
2 changed files with 41 additions and 33 deletions
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2
mllib/src/main/scala/org/apache/spark/ml/feature/PolynomialExpansion.scala
View file

@ -46,7 +46,7 @@ class PolynomialExpansion(override val uid: String)
* @group param
*/
val degree = new IntParam(this, "degree", "the polynomial degree to expand (>= 1)",
ParamValidators.gt(1))
ParamValidators.gtEq(1))
setDefault(degree -> 2)

72
mllib/src/test/scala/org/apache/spark/ml/feature/PolynomialExpansionSuite.scala
View file

@ -34,22 +34,31 @@ class PolynomialExpansionSuite
ParamsSuite.checkParams(new PolynomialExpansion)
}
private val data = Array(
Vectors.sparse(3, Seq((0, -2.0), (1, 2.3))),
Vectors.dense(-2.0, 2.3),
Vectors.dense(0.0, 0.0, 0.0),
Vectors.dense(0.6, -1.1, -3.0),
Vectors.sparse(3, Seq())
)
private val twoDegreeExpansion: Array[Vector] = Array(
Vectors.sparse(9, Array(0, 1, 2, 3, 4), Array(-2.0, 4.0, 2.3, -4.6, 5.29)),
Vectors.dense(-2.0, 4.0, 2.3, -4.6, 5.29),
Vectors.dense(new Array[Double](9)),
Vectors.dense(0.6, 0.36, -1.1, -0.66, 1.21, -3.0, -1.8, 3.3, 9.0),
Vectors.sparse(9, Array.empty, Array.empty))
private val threeDegreeExpansion: Array[Vector] = Array(
Vectors.sparse(19, Array(0, 1, 2, 3, 4, 5, 6, 7, 8),
Array(-2.0, 4.0, -8.0, 2.3, -4.6, 9.2, 5.29, -10.58, 12.17)),
Vectors.dense(-2.0, 4.0, -8.0, 2.3, -4.6, 9.2, 5.29, -10.58, 12.17),
Vectors.dense(new Array[Double](19)),
Vectors.dense(0.6, 0.36, 0.216, -1.1, -0.66, -0.396, 1.21, 0.726, -1.331, -3.0, -1.8,
-1.08, 3.3, 1.98, -3.63, 9.0, 5.4, -9.9, -27.0),
Vectors.sparse(19, Array.empty, Array.empty))
test("Polynomial expansion with default parameter") {
val data = Array(
Vectors.sparse(3, Seq((0, -2.0), (1, 2.3))),
Vectors.dense(-2.0, 2.3),
Vectors.dense(0.0, 0.0, 0.0),
Vectors.dense(0.6, -1.1, -3.0),
Vectors.sparse(3, Seq())
)
val twoDegreeExpansion: Array[Vector] = Array(
Vectors.sparse(9, Array(0, 1, 2, 3, 4), Array(-2.0, 4.0, 2.3, -4.6, 5.29)),
Vectors.dense(-2.0, 4.0, 2.3, -4.6, 5.29),
Vectors.dense(new Array[Double](9)),
Vectors.dense(0.6, 0.36, -1.1, -0.66, 1.21, -3.0, -1.8, 3.3, 9.0),
Vectors.sparse(9, Array.empty, Array.empty))
val df = sqlContext.createDataFrame(data.zip(twoDegreeExpansion)).toDF("features", "expected")
val polynomialExpansion = new PolynomialExpansion()
@ -67,23 +76,6 @@ class PolynomialExpansionSuite
}
test("Polynomial expansion with setter") {
val data = Array(
Vectors.sparse(3, Seq((0, -2.0), (1, 2.3))),
Vectors.dense(-2.0, 2.3),
Vectors.dense(0.0, 0.0, 0.0),
Vectors.dense(0.6, -1.1, -3.0),
Vectors.sparse(3, Seq())
)
val threeDegreeExpansion: Array[Vector] = Array(
Vectors.sparse(19, Array(0, 1, 2, 3, 4, 5, 6, 7, 8),
Array(-2.0, 4.0, -8.0, 2.3, -4.6, 9.2, 5.29, -10.58, 12.17)),
Vectors.dense(-2.0, 4.0, -8.0, 2.3, -4.6, 9.2, 5.29, -10.58, 12.17),
Vectors.dense(new Array[Double](19)),
Vectors.dense(0.6, 0.36, 0.216, -1.1, -0.66, -0.396, 1.21, 0.726, -1.331, -3.0, -1.8,
-1.08, 3.3, 1.98, -3.63, 9.0, 5.4, -9.9, -27.0),
Vectors.sparse(19, Array.empty, Array.empty))
val df = sqlContext.createDataFrame(data.zip(threeDegreeExpansion)).toDF("features", "expected")
val polynomialExpansion = new PolynomialExpansion()
@ -101,6 +93,22 @@ class PolynomialExpansionSuite
}
}
test("Polynomial expansion with degree 1 is identity on vectors") {
val df = sqlContext.createDataFrame(data.zip(data)).toDF("features", "expected")
val polynomialExpansion = new PolynomialExpansion()
.setInputCol("features")
.setOutputCol("polyFeatures")
.setDegree(1)
polynomialExpansion.transform(df).select("polyFeatures", "expected").collect().foreach {
case Row(expanded: Vector, expected: Vector) =>
assert(expanded ~== expected absTol 1e-1)
case _ =>
throw new TestFailedException("Unmatched data types after polynomial expansion", 0)
}
}
test("read/write") {
val t = new PolynomialExpansion()
.setInputCol("myInputCol")