这是我在stakcoverflow上的第一篇文章，因为我找不到解决此消息的线索“'PipelinedRDD'对象没有属性'_jdf'”，当我在火车数据集上调用trainer.fit以在Spark下创建神经网络模型时出现在Python中
这是我的代码
from pyspark import SparkContext
from pyspark.ml.classification import MultilayerPerceptronClassifier, MultilayerPerceptronClassificationModel
from pyspark.mllib.feature import StandardScaler
from pyspark.mllib.regression import LabeledPoint
from pyspark.sql import SQLContext
from pyspark.ml.evaluation import MulticlassClassificationEvaluator
### Import data in Spark ###
RDD_RAWfileWH= sc.textFile("c:/Anaconda2/Cognet/Data_For_Cognet_ready.csv")
header = RDD_RAWfileWH.first()
# Delete header from RAWData
RDD_RAWfile1 = RDD_RAWfileWH.filter(lambda x: x != header)
# Split each line of the RDD
RDD_RAWfile = RDD_RAWfile1.map(lambda line:[float(x) for x in line.split(',')])
FinalData = RDD_RAWfile.map(lambda row: LabeledPoint(row[0],[row[1:]]))
(trainingData, testData) = FinalData.randomSplit([0.7, 0.3])
layers = [15, 2, 3] …