scikit-learn_bench
scikit-learn_bench copied to clipboard
scikit-learn_bench benchmarks various implementations of machine learning algorithms across data analytics frameworks. It currently support the scikit-learn, DAAL4PY, cuML, and XGBoost frameworks for...
When benchmark using [xgb_cpu_main_config.json](https://github.com/IntelPython/scikit-learn_bench/blob/master/configs/xgboost/xgb_cpu_main_config.json). The following datasets are missing ``` WARNING: Dataset mlsr could not be loaded. Check the correct name or expand the download in the folder dataset. INFO:...
CPU and GPU configs for XGBoost have only few differences: in `data-format` (pandas vs cudf) and `tree-method` (hist vs gpu_hist). Dispatching for them with `--devices(s)` argument will simplify configs.
FULL ML Supervised Cheatsheat
Please create PRs for addressing code quality issues reported by codefactor scans https://www.codefactor.io/repository/github/IntelPython/scikit-learn_bench Some problems are simple fixes and i would expect that they can be fixed across entire repo...
Add benchmark, configs and update readme for scikit-learn HistGradientBoostingRegresssor and HistGradientBoostingClassifier benchmark.
Add benchmark and config for Catboost modelbuilder.
Here's some important updates for xgb and lgbm model converters bench + better parameters for gpu measurements to avoid Out Of Memory error on v100 machines
Hi! Is there a reason HistGradientBoostingEstimator from sklearn is not included in the benchmark? It should be about as fast as XGBoost.
If I try to run benchmarks with the command like ```sh python runner.py --configs configs/skl_xpu_config.json ``` it should run a patched version of scikit-learn algorithms. However, if scikit-learn-intelex package is...