我用Pypsark創(chuàng)建了一個kmeans算法。現(xiàn)在，我還想提取集群中心。如何將其包含在管道中？這是我到目前為止擁有的代碼，但它給我?guī)砹艘粋€錯誤“AttributeError：'PipelineModel'對象沒有屬性'clusterCenters'。如何修復？#### 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()
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aluckdog
TA貢獻1847條經(jīng)驗 獲得超7個贊
虛擬數(shù)據(jù)
from pyspark.ml.linalg import Vectors
from pyspark.ml.clustering import KMeans, KMeansModel
from pyspark.ml.pipeline import Pipeline
data = [(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"])
您的代碼
kmeans = KMeans() \
.setK(3) \
.setFeaturesCol("scaledFeatures")\
.setPredictionCol("cluster")
# Chain indexer and tree in a Pipeline
pipeline = 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.])]
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