我使用 PySpark 创建了一个 K-means 算法。现在，我想提取聚类中心。我该如何在管道中包含它？这是我目前的代码，但它抛出了一个错误 ‘AttributeError: ‘PipelineModel’ 对象没有属性 ‘clusterCenters’。如何修复这个问题？

#### model K-Means ###from pyspark.ml.clustering import KMeans, KMeansModelkmeans = KMeans() \          .setK(3) \          .setFeaturesCol("scaledFeatures")\          .setPredictionCol("cluster")# Chain indexer and tree in a Pipelinepipeline = Pipeline(stages=[kmeans])model = pipeline.fit(matrix_normalized)cluster = model.transform(matrix_normalized)#get cluster centerscenters = model.clusterCenters()

回答：

虚拟数据

from pyspark.ml.linalg import Vectorsfrom pyspark.ml.clustering import KMeans, KMeansModelfrom pyspark.ml.pipeline import Pipelinedata = [(Vectors.dense([0.0, 0.0]),), (Vectors.dense([1.0, 1.0]),),        (Vectors.dense([9.0, 8.0]),), (Vectors.dense([8.0, 9.0]),)]matrix_normalized = spark.createDataFrame(data, ["scaledFeatures"])

你的代码

kmeans = KMeans() \          .setK(3) \          .setFeaturesCol("scaledFeatures")\          .setPredictionCol("cluster")# Chain indexer and tree in a Pipelinepipeline = Pipeline(stages=[kmeans])model = pipeline.fit(matrix_normalized)cluster = model.transform(matrix_normalized)

只需更改最后一行

model.stages[0].clusterCenters()[array([0.5, 0.5]), array([8., 9.]), array([9., 8.])]