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mljar / mljar-supervised

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
https://mljar.com
MIT License
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AutoMlException #144

Closed Amri95 closed 4 years ago

Amri95 commented 4 years ago

AutoMLException: The algorithm Random Forest is not allowed to use for ML task: multiclass_classification. Allowed algorithms: ['Decision Tree', 'Baseline', 'LightGBM', 'Extra Trees', 'CatBoost', 'Linear', 'Neural Network', 'Nearest Neighbors']

pplonski commented 4 years ago

Thank you @Amri95 for reporting! Are you using the latest version of the package?

Amri95 commented 4 years ago

Hello, Thank you for your response. I am using version 0.6.0

Could you please explain the Ensemble?

On Tue, Aug 18, 2020 at 2:43 PM Piotr notifications@github.com wrote:

Thank you @Amri95 https://github.com/Amri95 for reporting! Are you using the latest version of the package?

— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub https://github.com/mljar/mljar-supervised/issues/144#issuecomment-675264706, or unsubscribe https://github.com/notifications/unsubscribe-auth/AI3T24QLD2HA7MT4HRY23VTSBIIHLANCNFSM4QCZTFSA .

pplonski commented 4 years ago

Could you paste some code example to reproduce?

The Ensemble method is based on http://www.cs.cornell.edu/~alexn/papers/shotgun.icml04.revised.rev2.pdf - it is a greedy approach.

pplonski commented 4 years ago

@Amri95 could you please provide some code sample, so I can reproduce. Thanks!

pplonski commented 4 years ago

I'm closing this issue. I can't reproduce it with the current code from master.