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catboost

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aaronmarkham
aaronmarkham commented Dec 6, 2019

I tried building the docs, but was met with a graphviz error. Typically this means I can spend a few hours pecking away at the dependencies until I get stable build... or someone that has it working can export their environment, and publish an environment.yml that we can use with the build instructions.
I was going off of the d2l book since that's a dep here, but their [environment.yml](https://g

ebubae
ebubae commented Feb 19, 2020

Is your feature request related to a problem? Please describe.
When generating generating targeted attacks the method arguments generate(x, y=None) can be confusing. In this case y usually refers to the target label for the attack, but users may accidentally put the correct label there, rendering the attack ineffective.

Describe the solution you'd like
Maybe we should change that

awesome-decision-tree-papers
hyperparameter_hunter
HunterMcGushion
HunterMcGushion commented Feb 19, 2019
  • Unable to supply validation_data to a Keras CVExperiment via model_extra_params[“fit”]
  • This is because HyperparameterHunter automatically sets validation_data to be the OOF data produced by the cross validation scheme
  • I can imagine this would be unexpected behavior, so I’d love to hear any thoughts on how to clear this up

Note

  • This issue (along with several others) was ori
awesome-gradient-boosting-papers
RemixAutoML

Demo on the capability of Yandex CatBoost gradient boosting classifier on a fictitious IBM HR dataset obtained from Kaggle. Data exploration, cleaning, preprocessing and model tuning are performed on the dataset

  • Updated Dec 5, 2019
  • Jupyter Notebook

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