Yesterday I wrote about how easy is to use Model Builder to create Machine Learning models directly from data inside Visual Studio.
If you prefer to work with command line interfaces, Machine Learning.Net AutoML also have a CLI interface and with a couple of commands, you can get some amazing results.
So, for this test I follow the tutorial [Auto generate a binary classifier using the CLI] and make some changes to the original command
> mlnet auto-train --task binary-classification --dataset "yelp_labelled.txt" --label-column-index 1 --has-header false --max-exploration-time 10
I’m using the same set of data I used yesterday and, my command is
mlnet auto-train --task regression --dataset "AgeRangeData03_AgeGenderLabelEncodedMoreData.csv" --label-column-index 2 --has-header true --max-exploration-time 60
The output is also interesting: it suggest to use a FastTree Regression trainer
My yesterday test using the IDE suggested a LightBGM regression trainer.
So, I decided to run the CLI one more time with some more processing time. This time the result is also a FastTree Tegression trainer.
Unless you need to use Visual Studio, this option is amazing for fast tests and you can also use the generated projects!
Greetings @ Toronto