Fixed parameters used in the Syn3A model.

Figshare2026-01-27 更新2026-04-28 收录

生物学建模

参数优化

数据链接：

https://figshare.com/articles/dataset/_p_Fixed_parameters_used_in_the_Syn3A_model_p_/31163485 数据链接链接失效反馈

官方服务：

资源简介：

Values obtained through the pipeline in Fig A in S1 Text using data from Refs [79,93,94].

创建时间：

2026-01-27

ibm-research/rag-hpo-bench

检索增强生成

参数优化

该数据集名为RAG‑HPO Bench，包含了一篇关于检索增强生成（RAG）超参数优化方法分析的论文中的网格搜索结果。数据集涵盖了162种RAG配置在五个RAG QA数据集（AIArxiv、BioASQ、ClapNQ、MiniWiki和WatsonxQA）上的开发和测试分割的输出和评分。数据集还包括了不同配置的详细结果文件，探索的超参数空间（如块大小、块重叠、嵌入模型、Top-k和生成模型），以及

Hugging Face2026-01-19 更新120

Fractional Cross-Validation for Optimizing Hyperparameters of Supervised Learning Algorithms

机器学习

参数优化

K-fold cross-validation (CV) is a robust method for estimating generalization performance of supervised learning models. Although CV is more reliable than using a single hold-out test set, it is also

DataCite Commons2025-07-29 更新70

Hyperparameter values of the machine learning methods optimized with respect to the area under the precision-recall curve.

参数优化

不平衡分类

(XLSX)

NIAID Data Ecosystem60

TWM Data Files

知识图谱嵌入

参数优化

Data files containing the full outputs of all hyperparameter searches needed for TWM to simulate the KGE model ComplEx on 5 KGs -- CoDExSmall, DBpedia50 OpenEA, Kinships, and UMLS. Data is in a pre-pr

NIAID Data Ecosystem80

Hyperparameter optimization using 10-fold grid search CV for the filtered LMCH data dynamics using a 70:30 partition with feature selection.

参数优化

网格搜索交叉验证

Hyperparameter optimization using 10-fold grid search CV for the filtered LMCH data dynamics using a 70:30 partition with feature selection.

Figshare2024-05-16 更新70