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/*
* 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.feature
import org.apache.spark.SparkFunSuite
import org.apache.spark.mllib.linalg.Vectors
import org.apache.spark.mllib.regression.LabeledPoint
import org.apache.spark.mllib.util.MLlibTestSparkContext
import org.apache.spark.util.Utils
class ChiSqSelectorSuite extends SparkFunSuite with MLlibTestSparkContext {
/*
* Contingency tables
* feature0 = {8.0, 0.0}
* class 0 1 2
* 8.0||1|0|1|
* 0.0||0|2|0|
*
* feature1 = {7.0, 9.0}
* class 0 1 2
* 7.0||1|0|0|
* 9.0||0|2|1|
*
* feature2 = {0.0, 6.0, 8.0, 5.0}
* class 0 1 2
* 0.0||1|0|0|
* 6.0||0|1|0|
* 8.0||0|1|0|
* 5.0||0|0|1|
*
* Use chi-squared calculator from Internet
*/
test("ChiSqSelector transform test (sparse & dense vector)") {
val labeledDiscreteData = sc.parallelize(
Seq(LabeledPoint(0.0, Vectors.sparse(3, Array((0, 8.0), (1, 7.0)))),
LabeledPoint(1.0, Vectors.sparse(3, Array((1, 9.0), (2, 6.0)))),
LabeledPoint(1.0, Vectors.dense(Array(0.0, 9.0, 8.0))),
LabeledPoint(2.0, Vectors.dense(Array(8.0, 9.0, 5.0)))), 2)
val preFilteredData =
Set(LabeledPoint(0.0, Vectors.dense(Array(0.0))),
LabeledPoint(1.0, Vectors.dense(Array(6.0))),
LabeledPoint(1.0, Vectors.dense(Array(8.0))),
LabeledPoint(2.0, Vectors.dense(Array(5.0))))
val model = new ChiSqSelector(1).fit(labeledDiscreteData)
val filteredData = labeledDiscreteData.map { lp =>
LabeledPoint(lp.label, model.transform(lp.features))
}.collect().toSet
assert(filteredData == preFilteredData)
}
test("model load / save") {
val model = ChiSqSelectorSuite.createModel()
val tempDir = Utils.createTempDir()
val path = tempDir.toURI.toString
try {
model.save(sc, path)
val sameModel = ChiSqSelectorModel.load(sc, path)
ChiSqSelectorSuite.checkEqual(model, sameModel)
} finally {
Utils.deleteRecursively(tempDir)
}
}
}
object ChiSqSelectorSuite extends SparkFunSuite {
def createModel(): ChiSqSelectorModel = {
val arr = Array(1, 2, 3, 4)
new ChiSqSelectorModel(arr)
}
def checkEqual(a: ChiSqSelectorModel, b: ChiSqSelectorModel): Unit = {
assert(a.selectedFeatures.deep == b.selectedFeatures.deep)
}
}
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