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General ML benchmarks, tabular data, AutoML, recommendation systems, anomaly detection, evaluation suites
166,252 datasets
Ablation study results comparing an Edge Graph Attention Network (EGAT) model against GRU, MLP, and LSTM methods for power load forecasting. The 5.5 KB XLS file, authored by Mengze Gu and last updated in April 2026, contains results from a study that transforms time series into graph features. The study demonstrates EGAT's effectiveness in finding important features and understanding complex time patterns for energy demand prediction.
Simulation results from a study proposing a graph-based method for high-accuracy power load forecasting. The 5.5 KB Excel file, authored by Mengze Gu and last updated in April 2026, compares the performance of an Edge Graph Attention Network (EGAT) against traditional models like GRU, MLP, and LSTM.
Case 2 simulation results by Mengze Gu, last updated April 23, 2026. The dataset contains results from a study proposing an Edge Graph Attention Network (EGAT) for power load forecasting, comparing it against GRU, MLP, and LSTM models. The data is stored in a 5.5 KB XLS file.
5.5 KB of simulation results from Mengze Gu's 2026 research comparing a novel Edge Graph Attention Network (EGAT) model against traditional methods for power load forecasting. The dataset likely contains the performance metrics from experiments that transformed time series data into graph features to capture complex multi-dimensional relationships. These results demonstrate the EGAT model's potential for improving forecasting accuracy by understanding complex time patterns.
Payroll expenditures for Colorado Department of Transportation for the current and previous state fiscal year. The dataset is provided by data.colorado.gov and was last updated on 2026-05-29. It includes columns for Employee, Amount, Job Description, Area Description, and Fiscal Year.
Legacy product from the Australian Ocean Data Network, published on data_gov_au. The dataset likely documents equipment and operations from oceanographic investigations conducted by the Hawaii Institute of Geophysics around 1970. The raw description states no abstract is available, and detailed metadata is minimal.
A directory of educational institutions in the municipality of Yopal, Colombia, for the year 2026. The dataset is provided by the digital government of Yopal-Casanare via the datos.gov.co platform. It was last updated on May 18, 2026.
Legacy product from the 1980 Heard Island Expedition, published by the Australian Ocean Data Network. The dataset likely contains marine geophysical observations and preliminary results from the expedition. Metadata is minimal; the actual data content requires verification after download.
February to May 1973 cruise data collected in Bass Strait and Tasmanian waters. The dataset is published by the Australian Ocean Data Network and appears to contain marine geology and oceanographic survey information. Legacy product metadata indicates no abstract is available for this historical collection.
Processed image subsets from the LoDoPaB-CT dataset, used by the GLIMPSE research paper. The dataset contains training and test slices stored as .npy float32 arrays, along with out-of-distribution brain images in .jpg format. It was uploaded by AmirEhsan1995 to Hugging Face and was last updated on June 7, 2026.
Nine Amazonian tree species were analyzed for leaf carbon, nitrogen, leaf area index, and carbon isotope ratios in 2001. The dataset, produced by NASA, contains measurements from the youngest and oldest leaves of sampled branches at the Manaus ZF2 Jacaranda transect in Brazil. It is available as a comma-delimited file.
Legacy product - no abstract available. The dataset is a report from a planning workshop held in February 1997 at Gold Creek Homestead, Gungahlin, ACT. It was published on the data_gov_au platform by the Australian Ocean Data Network.
The Australian offshore compilation is a geospatial dataset for the Circum-Pacific Map Project's Southwest Quadrant. It was published by the Australian Ocean Data Network on data_gov_au. The dataset is a legacy product from May 1978, and its abstract is not available.
A dataset from 221 patients with cervical cancer who underwent pelvic lymphadenectomy at the Affiliated Hospital of North Sichuan Medical College between January 2023 and September 2024. It contains clinical characteristics and laboratory data used to develop and validate machine learning models for predicting symptomatic pelvic lymphocele, which occurred in 44 patients (19.9%). The dataset was published by Yiyue Wang on figshare.
221 patient records from a retrospective analysis at the Affiliated Hospital of North Sichuan Medical College, collected between January 2023 and September 2024. The dataset was used to develop and validate interpretable machine learning models for predicting symptomatic pelvic lymphocele, with an incidence rate of 19.9% in the cohort. Author Yiyue Wang published the supporting data on figshare under a CC-BY-4.0 license.
19.9% of 221 cervical cancer patients developed symptomatic pelvic lymphocele after pelvic lymphadenectomy at a Chinese hospital between January 2023 and September 2024. Yiyue Wang created this dataset to develop interpretable machine learning models, with the K-Nearest Neighbors model achieving an AUC of 0.952 on the training set. The data includes clinical characteristics and laboratory results used to identify key predictive features like diabetes and tumor size.
Table 1_An interpretable machine learning model for predicting symptomatic pelvic lymphocele after pelvic lymphadenectomy in cervical cancer.xls contains clinical and laboratory data from 221 patients with cervical cancer. The data was collected at the Affiliated Hospital of North Sichuan Medical College between January 2023 and September 2024. Author Yiyue Wang published the dataset on figshare under a CC-BY-4.0 license.
19.9% of the 221 cervical cancer patients studied developed symptomatic pelvic lymphocele after surgery. The dataset contains clinical characteristics and laboratory data from a retrospective analysis at the Affiliated Hospital of North Sichuan Medical College, collected between January 2023 and September 2024. It was used to develop and validate interpretable machine learning models for predicting this surgical complication.
1996 extended abstracts from the 13th Australian Geological Convention in Canberra, focusing on Australia and the Ocean Drilling Program. The collection is published on data_gov_au by the Australian Ocean Data Network. The data is available in HTML and PDF formats.
Kexin Zhang published a 6.6 MB dataset on figshare in 2026 to support manuscript reproducibility. The data includes processed numerical simulation and experimental results for structural health monitoring of offshore wind turbine towers. It contains finite element modal frequency data, axial crack indicators, annular crack indicators, flange bolt fracture indicators, experimental frequency data, and experimental SSMR indicator data.