lightgbm
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Version
com.microsoft.ml.spark:mmlspark_2.11:jar:0.18.1
spark= 2.4.3
scala=2.11.12
data (csv with header) https://gist.github.com/ttpro1995/69051647a256af912803c9a16040f43a
download data and save as csv file, put into folder /data/public/HIGGS/higgs.test.predictioncsv
val data = spark.read.option("header","true").option("inferSchema", "true").csv("/data/public/HIGGS
Support DataFrame.select_dtypes
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I'm sorry if I missed this functionality, but CLI version hasn't it for sure (I saw the related code only in generate_code_examples.py). I guess it will be very useful to eliminate copy-paste phase, especially for large models.
Of course, piping is a solution, but not for development in Jupyter Notebook, for example.
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It will be nice to have Exploratory Data Analysis (EDA) similar that is in https://mljar.com

The EDA can be saved in a separate Markdown file and have link to it from the main AutoML readme.
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One unit test in the R package is currently broken. Steps to reproduce on Mac
This results in the following error at the ends of the logs