PN 6

SimTech EXC 2075 Project Network 6 "Machine learning for simulation"

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4,301 to 4,310 of 4,903 Results

tasks.tar.gz Nov 5, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data [NeurIPS, arXiv v2] Plain Text - 3.5 GB - MD5: aee96049f206a64cf9002749f238a8b9 DATA Folder with imported datasets, with restricted access for copyright reasons.
XGB-HPO_steps.tar.gz Nov 5, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data [NeurIPS, arXiv v2] Plain Text - 120.7 GB - MD5: 7c82fcd9a59eac9f2736d02970010233 DATA
Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data Aug 8, 2024 - PN 6-3 Holzmüller, David; Grinsztajn, Léo; Steinwart, Ingo, 2024, "Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data", https://doi.org/10.18419/DARUS-4255, DaRUS, V1 This dataset contains code and data for our paper "Better by default: Strong pre-tuned MLPs and boosted trees on tabular data". The main code is provided in pytabkit_code.zip and contains further documentation in README.md and the docs folder. The main code is also provided on GitHub. Here, we additionally provide the data that is generated by the...
CatBoost-HPO_steps.tar.gz Aug 8, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data Plain Text - 129.4 GB - MD5: 18626c6d8e091db924ce74542bb7df80 DATA
grinsztajn_benchmarking_code.zip Aug 8, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data ZIP Archive - 1.1 MB - MD5: e4e6f5dca291e6c59f5135ab1a1d63a8 Code for running the Grinsztajn. et al (2022) benchmark with our models.
grinsztajn_results.csv.gz Aug 8, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data Gzip Archive - 87.2 MB - MD5: 04efd949409a882d3fb3c18371d451fa Results on the Grinsztajn et al. (2022) benchmark.
LGBM-HPO_steps.tar.gz Aug 8, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data Plain Text - 107.9 GB - MD5: 63faf9208e0831c1eeda073b73302ccf DATA
main_no_results.tar.gz Aug 8, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data Plain Text - 555.1 MB - MD5: 9e1b8e3d2f905725b90fd498435245e4 DATA Benchmark results data for meta-train and meta-test benchmarks. Contains result summaries (enough for plotting) but not the detailed results.
main_results.tar.gz Aug 8, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data Plain Text - 260.5 GB - MD5: 147bd2b84a688a65e752a0b93af36424 DATA Detailed results, including predictions on datasets and best parameters, for all main methods. This excludes the data for individual hyperparameter optimization (HPO) steps, which is provided separately.
MLP-RTDL-HPO_steps.tar.gz Aug 8, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data Plain Text - 126.1 GB - MD5: 07ccbba1805898909d5c75df01fd847d DATA

tasks.tar.gz

Nov 5, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data [NeurIPS, arXiv v2]

Plain Text - 3.5 GB -

DATA

Folder with imported datasets, with restricted access for copyright reasons.

XGB-HPO_steps.tar.gz

Nov 5, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data [NeurIPS, arXiv v2]

Plain Text - 120.7 GB -

DATA

Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data

Aug 8, 2024 - PN 6-3

Holzmüller, David; Grinsztajn, Léo; Steinwart, Ingo, 2024, "Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data", https://doi.org/10.18419/DARUS-4255, DaRUS, V1

This dataset contains code and data for our paper "Better by default: Strong pre-tuned MLPs and boosted trees on tabular data". The main code is provided in pytabkit_code.zip and contains further documentation in README.md and the docs folder. The main code is also provided on GitHub. Here, we additionally provide the data that is generated by the...

CatBoost-HPO_steps.tar.gz

Aug 8, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data

Plain Text - 129.4 GB -

DATA

grinsztajn_benchmarking_code.zip

Aug 8, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data

ZIP Archive - 1.1 MB -

Code for running the Grinsztajn. et al (2022) benchmark with our models.

grinsztajn_results.csv.gz

Aug 8, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data

Gzip Archive - 87.2 MB -

Results on the Grinsztajn et al. (2022) benchmark.

LGBM-HPO_steps.tar.gz

Aug 8, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data

Plain Text - 107.9 GB -

DATA

main_no_results.tar.gz

Aug 8, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data

Plain Text - 555.1 MB -

DATA

Benchmark results data for meta-train and meta-test benchmarks. Contains result summaries (enough for plotting) but not the detailed results.

main_results.tar.gz

Aug 8, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data

Plain Text - 260.5 GB -

DATA

Detailed results, including predictions on datasets and best parameters, for all main methods. This excludes the data for individual hyperparameter optimization (HPO) steps, which is provided separately.

MLP-RTDL-HPO_steps.tar.gz

Aug 8, 2024 - Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data

Plain Text - 126.1 GB -

DATA

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