Is there a way to get the significance level of each coefficient we receive after we fit a logistic regression model on training data?
I was trying to find out a way and could not figure out myself.
I think I may get the significance level of each feature if I run chi sq test but first of all not sure if I can run the test on all features together and secondly I have numeric data value so if it will give me right result or not that remains a question as well.
Right now I am running the modeling part using statsmodel and scikit learn but certainly, want to know, how can I get these results from PySpark ML or MLLib itself
If anyone can shed some light, it will be helpful
I use only mllib, I think that when you train a model you can use toPMML method to export your model un PMML format (xml file), then you can parse the xml file to get features weights, here an example
https://spark.apache.org/docs/2.0.2/mllib-pmml-model-export.html
Hope that will help