P-values for Spark Logistic Regression












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I am trying to find the p-values for coefficients for Spark 2.3 Logistic Regression. Specifically, if I do:



lr = LogisticRegression(labelCol="clicks", featuresCol="features", maxIter=10,elasticNetParam=1)
# Train model with Training Data
lrModel = lr.fit(trainingData)
print(lrModel.coefficients) #get coefficients


will return a list of the coefficient values, but without a p-value or confidence interval. I could not find in the documentation (https://spark.apache.org/docs/latest/api/python/pyspark.ml.html) where p-values for coefficients could be found.



Similir Questions that do not answer what I am looking for:



How to calculate p-values in Spark's Logistic Regression?
(This is an older version of Spark, and I could not confirm if it actually returns a pvalue; also note that that function does not take in pipelines (e.g. one hot encoding pipelines etc.))










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    I am trying to find the p-values for coefficients for Spark 2.3 Logistic Regression. Specifically, if I do:



    lr = LogisticRegression(labelCol="clicks", featuresCol="features", maxIter=10,elasticNetParam=1)
    # Train model with Training Data
    lrModel = lr.fit(trainingData)
    print(lrModel.coefficients) #get coefficients


    will return a list of the coefficient values, but without a p-value or confidence interval. I could not find in the documentation (https://spark.apache.org/docs/latest/api/python/pyspark.ml.html) where p-values for coefficients could be found.



    Similir Questions that do not answer what I am looking for:



    How to calculate p-values in Spark's Logistic Regression?
    (This is an older version of Spark, and I could not confirm if it actually returns a pvalue; also note that that function does not take in pipelines (e.g. one hot encoding pipelines etc.))










    share|improve this question



























      0












      0








      0







      I am trying to find the p-values for coefficients for Spark 2.3 Logistic Regression. Specifically, if I do:



      lr = LogisticRegression(labelCol="clicks", featuresCol="features", maxIter=10,elasticNetParam=1)
      # Train model with Training Data
      lrModel = lr.fit(trainingData)
      print(lrModel.coefficients) #get coefficients


      will return a list of the coefficient values, but without a p-value or confidence interval. I could not find in the documentation (https://spark.apache.org/docs/latest/api/python/pyspark.ml.html) where p-values for coefficients could be found.



      Similir Questions that do not answer what I am looking for:



      How to calculate p-values in Spark's Logistic Regression?
      (This is an older version of Spark, and I could not confirm if it actually returns a pvalue; also note that that function does not take in pipelines (e.g. one hot encoding pipelines etc.))










      share|improve this question















      I am trying to find the p-values for coefficients for Spark 2.3 Logistic Regression. Specifically, if I do:



      lr = LogisticRegression(labelCol="clicks", featuresCol="features", maxIter=10,elasticNetParam=1)
      # Train model with Training Data
      lrModel = lr.fit(trainingData)
      print(lrModel.coefficients) #get coefficients


      will return a list of the coefficient values, but without a p-value or confidence interval. I could not find in the documentation (https://spark.apache.org/docs/latest/api/python/pyspark.ml.html) where p-values for coefficients could be found.



      Similir Questions that do not answer what I am looking for:



      How to calculate p-values in Spark's Logistic Regression?
      (This is an older version of Spark, and I could not confirm if it actually returns a pvalue; also note that that function does not take in pipelines (e.g. one hot encoding pipelines etc.))







      apache-spark databricks






      share|improve this question















      share|improve this question













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      share|improve this question








      edited Nov 13 '18 at 3:05







      Josh

















      asked Nov 13 '18 at 2:53









      JoshJosh

      798




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