How to load logistic regression model?

Question

I want to train the logistic regression model using Apache Spark in Java. As first step I would like to train the model just once and save the model parameters (intercept and Coefficient). Subsequently use the saved model parameters to score at a later point in time. I am able to save the model in parquet file, using the following code

LogisticRegressionModel trainedLRModel = logReg.fit(data);
trainedLRModel.write().overwrite().save("mypath");

When I load the model to score, I get the following error.

LogisticRegression lr = new LogisticRegression();
lr.load("//saved_model_path");

Exception in thread "main" java.lang.NoSuchMethodException: org.apache.spark.ml.classification.LogisticRegressionModel.<init>(java.lang.String)
    at java.lang.Class.getConstructor0(Class.java:3082)
    at java.lang.Class.getConstructor(Class.java:1825)
    at org.apache.spark.ml.util.DefaultParamsReader.load(ReadWrite.scala:325)
    at org.apache.spark.ml.util.MLReadable$class.load(ReadWrite.scala:215)
    at org.apache.spark.ml.classification.LogisticRegression$.load(LogisticRegression.scala:672)
    at org.apache.spark.ml.classification.LogisticRegression.load(LogisticRegression.scala)

Is there a way to train and save model and then evaluate(score) later? I am using Spark ML 2.1.0 in Java.

Answer 1

I face the same problem with pyspark 2.1.1, when i change from LogisticRegression to LogisticRegressionModel , everything works well.

LogisticRegression.load("/model/path") # not works 

LogisticRegressionModel.load("/model/path") # works well