As databases grow larger, it becomes harder to fully control their collection, and they frequently come with missing values: incomplete observations. These large databases are well suited to train mac

DataCite Commons2025-05-26 更新40

Mele0/SynLV

纵向生存预测

缺失数据处理方法

SynLV v1.0是一个用于评估纵向生存模型在不完整最终遭遇下的鲁棒性的合成基准工具。该版本包括9个主要场景和每个场景的5个队列种子。每个场景/种子目录包含训练、验证和测试集的Parquet文件以及元数据文件。数据集旨在用于在不完整最后访问情况下的鲁棒性基准测试，并使用固定的场景和分割约定进行可重复评估。

Hugging Face2026-05-04 更新30

Additional file 1 of Tensor extrapolation: an adaptation to data sets with missing entries

张量外推

缺失数据处理方法

Additional file 1. Python code. The notebook highlights core components of the code applied in the study.

Figshare2022-02-25 更新50

Mean Error (ME) and Root Mean Square Error (RMSE) between OTSun simulations and the reference models.

太阳辐射模拟

模型误差评估

Mean Error (ME) and Root Mean Square Error (RMSE) between OTSun simulations and the reference models.

NIAID Data Ecosystem40