[SPARK-25624][TEST] Reduce test time of LogisticRegressionSuite.multinomial logistic regression…

[shahidki31]

… with intercept with elasticnet regularization

What changes were proposed in this pull request?

In the test, "multinomial logistic regression with intercept with elasticnet regularization" in the "LogisticRegressionSuite", taking around 1 minute to train 2 logistic regression model.
However after analyzing the training cost over iteration, we can reduce the computation time by 50%.
Training cost vs iteration for model 1

So, model1 is converging after iteration 200.

Training cost vs iteration for model 2:

After around 50 iteration, model2 is converging.
So, if we give maximum iteration for model1 and model2 as 220 and 90 respectively, we can reduce the computation time by half.

How was this patch tested?

Computation time in local setup :
Before change:
~54 sec
After change:
~35 sec

(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
(If this patch involves UI changes, please attach a screenshot; otherwise, remove this)

Please review http://spark.apache.org/contributing.html before opening a pull request.

[AmplabJenkins]

Can one of the admins verify this patch?

[shahidki31]

cc @srowen Kindly review. I have done the same approach in the PR, #22659

[srowen]

This kind of thing looks OK, but please make one PR. There's no point in opening lots of JIRAs and PRs for the same change in N places.

[shahidki31]

Thanks for the suggestion. I will close this and amend in the other PR.