我正在运行一个非常简单的Spark(在Databricks上为2.4.0)ML脚本:
from pyspark.ml.clustering import LDA
lda = LDA(k=10, maxIter=100).setFeaturesCol('features')
model = lda.fit(dataset)
但是收到以下错误:
IllegalArgumentException: 'requirement failed: Column features must be of type equal to one of the following types: [struct<type:tinyint,size:int,indices:array<int>,values:array<double>>, array<double>, array<float>] but was actually of type array<double>.'
为什么我的array<double>
不是array<double>
?
以下是架构:
root
|-- BagOfWords: struct (nullable = true)
| |-- indices: array (nullable = true)
| | |-- element: long (containsNull = true)
| |-- size: long (nullable = true)
| |-- type: long (nullable = true)
| |-- values: array (nullable = true)
| | |-- element: double (containsNull = true)
|-- tokens: array (nullable = true)
| |-- element: string (containsNull = true)
|-- features: array (nullable = true)
| |-- element: double (containsNull = true)
答案 0 :(得分:1)
您可能需要使用矢量汇编器将其转换为矢量形式
from pyspark.ml.feature import VectorAssembler