【发布时间】:2018-05-04 22:31:09
【问题描述】:
我正在使用 paramGrid 来微调我的模型参数。这是以下代码。
windowSize = 5
minCount = 10
vectorSize=300
maxIter= [10,100,1000]
regParam= [0.1,0.01]
paramGrid = ParamGridBuilder() \
.addGrid(q1w2model.setWindowSize,windowSize) \
.addGrid(q1w2model.setMinCount,minCount) \
.addGrid(q2w2model.setWindowSize,windowSize) \
.addGrid(q2w2model.setMinCount,minCount) \
.addGrid(q1w2model.setVectorSize,vectorSize) \
.addGrid(q2w2model.setVectorSize,vectorSize) \
.addGrid(lr.setMaxIter,maxIter) \
.addGrid(lr.setRegParam, regParam) \
.build()
tvs = TrainValidationSplit(estimator=pipeline,
estimatorParamMaps=paramGrid,
evaluator=BinaryClassificationEvaluator(),
trainRatio=0.8)
model = tvs.fit(train) # model is the model with combination of parameters that performed best
以下是回溯调用:
文件“/home/PycharmProjects/untitled1/quora_feaures_pyspark.py”,第 406 行,在 .addGrid(lr.setRegParam, regParam) \ 文件“/usr/local/lib/python2.7/dist-packages/pyspark/ml/tuning.py”,第 115 行,在构建中 返回 [dict(zip(keys, prod)) for prod in itertools.product(*grid_values)] TypeError: 'int' 对象不可迭代
【问题讨论】:
标签: apache-spark pyspark pyspark-sql apache-spark-ml