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LightGBM

microsoft / LightGBM

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[R-package] use keyword arguments for all internal function calls

jameslamb
jameslamb commented Sep 13, 2020

Summary

Today in the R package, there are a lot of internal function calls which use only positional arguments. Change them to use keyword arguments for extra safety.

I've added this issue to provide a small, focused contribution opportunity for Hacktoberfest 2020 participants. If you are an experienced open source contributor, please leave this

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good first issue hacktoberfest r-package
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mmlspark

Azure / mmlspark

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[LightGBM] Regression: how to penalize negative predictions

3
brunocous
brunocous commented Sep 2, 2020

I have a simple regression task (using a LightGBMRegressor) where I want to penalize negative predictions more than positive ones. Is there a way to achieve this with the default regression LightGBM objectives (see https://lightgbm.readthedocs.io/en/latest/Parameters.html)? If not, is it somehow possible to define (many example for default LightGBM model) and pass a custom regression objective?

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LightGBM enhancement good first issue
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Trusted-AI / adversarial-robustness-toolbox

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Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference

python deep-neural-networks attack scikit-learn extraction artificial-intelligence xgboost lightgbm logistic-regression support-vector-machine decision-trees ibm-research poisoning adversarial-machine-learning catboost ibm-research-ai gradient-boosted-trees defense-methods codait trusted-ai
  • Updated Sep 17, 2020
  • Python

BayesWitnesses / m2cgen

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add option to save generated code into file

8
StrikerRUS
StrikerRUS commented Oct 18, 2019

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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enhancement good first issue
awesome-decision-tree-papers

benedekrozemberczki / awesome-decision-tree-papers

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A collection of research papers on decision, classification and regression trees with implementations.

classifier machine-learning random-forest statistical-learning xgboost lightgbm gradient-boosting-machine ensemble-learning cart decision-tree tree-ensemble decision-tree-classifier gradient-boosting classification-trees decision-tree-learning decision-tree-model classification-model catboost regression-tree machine-learning-research
  • Updated Aug 2, 2020
  • Python
awesome-gradient-boosting-papers

benedekrozemberczki / awesome-gradient-boosting-papers

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A curated list of gradient boosting research papers with implementations.

classifier machine-learning deep-learning random-forest h2o xgboost lightgbm gradient-boosting-machine adaboost decision-tree gradient-boosting-classifier classification-algorithm gradient-boosting boosting classification-trees xgboost-algorithm catboost gradient-boosted-trees classification-tree gradient-boosting-decision-trees
  • Updated Aug 2, 2020
  • Python

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