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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.ml.classification
import org.apache.spark.SparkFunSuite
import org.apache.spark.ml.linalg.{Vector, Vectors}
final class TestProbabilisticClassificationModel(
override val uid: String,
override val numFeatures: Int,
override val numClasses: Int)
extends ProbabilisticClassificationModel[Vector, TestProbabilisticClassificationModel] {
override def copy(extra: org.apache.spark.ml.param.ParamMap): this.type = defaultCopy(extra)
override protected def predictRaw(input: Vector): Vector = {
input
}
override protected def raw2probabilityInPlace(rawPrediction: Vector): Vector = {
rawPrediction
}
def friendlyPredict(input: Vector): Double = {
predict(input)
}
}
class ProbabilisticClassifierSuite extends SparkFunSuite {
test("test thresholding") {
val thresholds = Array(0.5, 0.2)
val testModel = new TestProbabilisticClassificationModel("myuid", 2, 2)
.setThresholds(thresholds)
assert(testModel.friendlyPredict(Vectors.dense(Array(1.0, 1.0))) === 1.0)
assert(testModel.friendlyPredict(Vectors.dense(Array(1.0, 0.2))) === 0.0)
}
test("test thresholding not required") {
val testModel = new TestProbabilisticClassificationModel("myuid", 2, 2)
assert(testModel.friendlyPredict(Vectors.dense(Array(1.0, 2.0))) === 1.0)
}
}
object ProbabilisticClassifierSuite {
/**
* Mapping from all Params to valid settings which differ from the defaults.
* This is useful for tests which need to exercise all Params, such as save/load.
* This excludes input columns to simplify some tests.
*/
val allParamSettings: Map[String, Any] = ClassifierSuite.allParamSettings ++ Map(
"probabilityCol" -> "myProbability",
"thresholds" -> Array(0.4, 0.6)
)
}
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