ml.dmlc.xgboost4j.scala.example.PredictLeafIndices.scala Maven / Gradle / Ivy
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/*
Copyright (c) 2014 by Contributors
Licensed 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 ml.dmlc.xgboost4j.scala.example
import java.util
import scala.collection.mutable
import ml.dmlc.xgboost4j.scala.{XGBoost, DMatrix}
object PredictLeafIndices {
def main(args: Array[String]): Unit = {
val trainMat = new DMatrix("../../demo/data/agaricus.txt.train?format=libsvm")
val testMat = new DMatrix("../../demo/data/agaricus.txt.test?format=libsvm")
val params = new mutable.HashMap[String, Any]()
params += "eta" -> 1.0
params += "max_depth" -> 2
params += "silent" -> 1
params += "objective" -> "binary:logistic"
val watches = new mutable.HashMap[String, DMatrix]
watches += "train" -> trainMat
watches += "test" -> testMat
val round = 3
val booster = XGBoost.train(trainMat, params.toMap, round, watches.toMap)
// predict using first 2 tree
val leafIndex = booster.predictLeaf(testMat, 2)
for (leafs <- leafIndex) {
println(java.util.Arrays.toString(leafs))
}
// predict all trees
val leafIndex2 = booster.predictLeaf(testMat, 0)
for (leafs <- leafIndex) {
println(java.util.Arrays.toString(leafs))
}
}
}