Pyspark 交叉验证中的问题

Question

我正在尝试在下面的代码中交叉验证 Pyspark 上的 RF 模型并抛出错误：

from pyspark.ml import Pipeline
from pyspark.ml.classification import RandomForestClassifier
from pyspark.ml.evaluation import MulticlassClassificationEvaluator
from pyspark.ml.tuning import ParamGridBuilder, CrossValidator

# Your code 
trainData = raw_data_ 
numFolds = 5 

rf = RandomForestClassifier(labelCol="Target", featuresCol="Scaled_features")
evaluator = MulticlassClassificationEvaluator() #    

pipeline = Pipeline(stages=[rf])
paramGrid = (ParamGridBuilder()\
    .addGrid(rf.numTrees, [3, 10])\
    .build())
crossval = CrossValidator(
    estimator=pipeline,
    estimatorParamMaps=paramGrid,
    evaluator=evaluator,
    numFolds=numFolds)

tr_model = crossval.fit(trainData)

但这会导致错误

我的 raw_data_ 变量是：

|            features|Position_Group|     Scaled_features|Target|
+--------------------+--------------+--------------------+------+
|[173.735992431640...|           FWD|[12.9261366722264...|     0|
|[188.975997924804...|           FWD|[14.0600087682323...|     0|
|[179.832000732421...|           FWD|[13.3796859647366...|     0|
|[155.752807617187...|           MID|[11.5881692110224...|     2|
|[176.783996582031...|           FWD|[13.1529113184815...|     0|
|[176.783996582031...|           MID|[13.1529113184815...|     2|
|[182.880004882812...|           FWD|[13.6064606109917...|     0|
|[182.880004882812...|           DEF|[13.6064606109917...|     1|
|[182.880004882812...|           FWD|[13.6064606109917...|     0|
|[182.880004882812...|           MID|[13.6064606109917...|     2|
|[188.975997924804...|           DEF|[14.0600087682323...|     1|
|[176.783996582031...|           MID|[13.1529113184815...|     2|
|[170.688003540039...|           MID|[12.6993631612409...|     2|
|[155.447998046875...|           FWD|[11.5654910652351...|     0|
|[188.975997924804...|           FWD|[14.0600087682323...|     0|
|[179.832000732421...|           MID|[13.3796859647366...|     2|
|[188.975997924804...|           MID|[14.0600087682323...|     2|
|[185.927993774414...|           FWD|[13.8332341219772...|     0|
|[176.783996582031...|           FWD|[13.1529113184815...|     0|
|[188.975997924804...|           DEF|[14.0600087682323...|     1|
+--------------------+--------------+--------------------+------+

关于问题发生的原因和位置有什么建议吗？如何解决这个问题？

谢谢

Answer 1

错误说

Error while calling evaluate. Field "label" does not exist.

这表明评估者出了点问题。在您定义的评估器中，您没有指定标签列，因此评估器尝试使用默认的“标签”列，但该列不存在。

要解决这个问题，您需要在实例化评估器时指定标签列，就像您为分类器所做的那样。例如

evaluator = MulticlassClassificationEvaluator(labelCol="Target")

Pyspark 交叉验证中的问题

Issue in Pyspark Cross Validation

apache-spark

pyspark

apache-spark-sql

cross-validation

apache-spark-ml