SelfExplainML / PiML-Toolbox

PiML (Python Interpretable Machine Learning) toolbox for model development & diagnostics
https://selfexplainml.github.io/PiML-Toolbox
Apache License 2.0
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Add New Feature Selectors and Set on data #16

Open HamedMZNN opened 1 year ago

HamedMZNN commented 1 year ago

Hi. I want to add different Feature Selectors and different Classifiers. I try from Arbitrary part, but my question is how can I select the one which I want to work with? I have started to work with this tool, and I couldn't find any file which have a complete explanation of this tool. Thanks

ZebinYang commented 1 year ago

Hi @HamedMZNN , I don't understand your request. Can you elaborate more about "different Feature Selectors and different Classifiers"? (better with some demo codes)

HamedMZNN commented 1 year ago

Hi Thanks for your reply. I mean, I want to add some Feature Selectors like VarianceThreshold and some classifiers like AdaBoost to this tool and compare their results by Gami and Glm and ReLu which you have in this tool. Is it possible or not that I can do this? Best Regards

On Fri, 7 Oct 2022 at 09:54, Zebin YANG @.***> wrote:

Hi @HamedMZNN https://github.com/HamedMZNN , I don't understand your request. Can you elaborate more about "different Feature Selectors and different Classifiers"? (better with some demo codes)

— Reply to this email directly, view it on GitHub https://github.com/SelfExplainML/PiML-Toolbox/issues/16#issuecomment-1271244499, or unsubscribe https://github.com/notifications/unsubscribe-auth/A3BUFYLPERPNKJI7LKHDV7DWB7JLFANCNFSM6AAAAAAQ5LXMKY . You are receiving this because you were mentioned.Message ID: @.***>

ZebinYang commented 1 year ago

Hi @HamedMZNN ,

You may write some scripts to do such kinds of feature engineering and model training. Just register the model and data into PiML using the demo at https://colab.research.google.com/github/SelfExplainML/PiML-Toolbox/blob/main/examples/Example_ExternalModels.ipynb#scrollTo=7WGJ8PzutkLh, "Scenario 2: Register external fitted models with dataset".