Benchmarks Alternatives
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A library for debugging/inspecting machine learning classifiers and explaining their predictions
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H2O
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
benchmarks discussion
benchmarks reviews and mentions
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[D] [R] Hyperparameter space for lightGBM
A good starting point could be the CatBoost quality benchmarks, which also tune LightGBM. You can find their hyperparameter settings here.
Stats
catboost/benchmarks is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of benchmarks is Jupyter Notebook.
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