spark JavaBisectingKMeansExample 源码
spark JavaBisectingKMeansExample 代码
文件路径：/examples/src/main/java/org/apache/spark/examples/ml/JavaBisectingKMeansExample.java
/*
* 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.examples.ml;
// $example on$
import org.apache.spark.ml.clustering.BisectingKMeans;
import org.apache.spark.ml.clustering.BisectingKMeansModel;
import org.apache.spark.ml.evaluation.ClusteringEvaluator;
import org.apache.spark.ml.linalg.Vector;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
// $example off$
import org.apache.spark.sql.SparkSession;
/**
* An example demonstrating bisecting k-means clustering.
* Run with
* <pre>
* bin/run-example ml.JavaBisectingKMeansExample
* </pre>
*/
public class JavaBisectingKMeansExample {
public static void main(String[] args) {
SparkSession spark = SparkSession
.builder()
.appName("JavaBisectingKMeansExample")
.getOrCreate();
// $example on$
// Loads data.
Dataset<Row> dataset = spark.read().format("libsvm").load("data/mllib/sample_kmeans_data.txt");
// Trains a bisecting k-means model.
BisectingKMeans bkm = new BisectingKMeans().setK(2).setSeed(1);
BisectingKMeansModel model = bkm.fit(dataset);
// Make predictions
Dataset<Row> predictions = model.transform(dataset);
// Evaluate clustering by computing Silhouette score
ClusteringEvaluator evaluator = new ClusteringEvaluator();
double silhouette = evaluator.evaluate(predictions);
System.out.println("Silhouette with squared euclidean distance = " + silhouette);
// Shows the result.
System.out.println("Cluster Centers: ");
Vector[] centers = model.clusterCenters();
for (Vector center : centers) {
System.out.println(center);
}
// $example off$
spark.stop();
}
}
相关信息
相关文章
spark JavaAFTSurvivalRegressionExample 源码
spark JavaBucketedRandomProjectionLSHExample 源码
spark JavaBucketizerExample 源码
spark JavaChiSqSelectorExample 源码
spark JavaChiSquareTestExample 源码
spark JavaCorrelationExample 源码
0
赞
热门推荐
-
2、 - 优质文章
-
3、 gate.io
-
6、 golang
-
7、 openharmony