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General ML benchmarks, tabular data, AutoML, recommendation systems, anomaly detection, evaluation suites
169,080 datasets
Table 7 contains facility-transportation proximity rates within a 1000-meter buffer zone. The dataset was authored by Tomofumi Yamazaki and is available under a CC-BY-4.0 license. It was last updated on May 29, 2026.
A 9.5 KB Excel file containing data on facility-transportation proximity rates within 500-meter buffer zones, authored by Tomofumi Yamazaki. The dataset was last updated on 2026-05-29 17:29:18 and is shared under a CC-BY-4.0 license on figshare.
A small dataset of 9.5 KB in XLS format contains facility-transportation proximity rates calculated within a 3000-meter buffer zone. It was authored by Tomofumi Yamazaki and last updated on May 29, 2026. The specific number of rows and column definitions are not provided in the metadata.
9.5 KB of tabular data in XLS format, uploaded by Tomofumi Yamazaki to figshare. The dataset describes facility-transportation proximity rates within a 250-meter buffer zone. It was last updated on 2026-05-29.
Maintenance frequency data for substation equipment recorded over a 12-month period. The dataset was authored by Yuping Yan and is available in an XLS format under a CC-BY-4.0 license. It was last updated on May 22, 2026.
Measurement invariance across sex (WLSMV) estimator is a dataset by Nouf Sahal Alharbi. The dataset is stored in an XLS file with a size of 5.5 KB. It was last updated on May 22, 2026.
Monthly legacy service performance data beginning in 2015, indicating the percent of required buses and operators available during peak periods. The dataset is published by data.ny.gov and was last updated on 2026-05-15. It contains columns such as AM/PM, Scheduled Buses, Operating Buses, Company, Month, and Monthly Pull Out.
A dataset from the Local Plan 2022 consultation evaluating neighbourhood parades. It contains scores based on the presence of key facilities, ATMs, national operators, and vacancy rates. The data was published by the Government Digital Service via the eu_open_data platform.
A dataset containing predictions for protein essentiality generated by the DLAM deep learning model. The model integrates domain composition, subcellular localization, orthology, gene expression, and protein-protein interaction data. The dataset was authored by Shunxian Zhou and last updated on April 14, 2026.
DLAM is a deep learning framework for predicting essential proteins, integrating domain composition, subcellular localization, orthology, and gene expression with a weighted protein-protein interaction network. The dataset contains model performance results, including ROC-AUC, AP, and F1-score, evaluated on the DIP and BioGRID datasets. It was authored by Shunxian Zhou and last updated on 2026-04 14.
Shunxian Zhou's research dataset, last updated April 2026, presents predictions for essential proteins using a deep learning model. The model integrates domain composition, subcellular localization, orthology, and gene expression with a protein-protein interaction network. Performance metrics, including ROC-AUC, AP, and F1-score, are reported from evaluations on the DIP and BioGRID datasets.
A 366.0 KB Excel file containing results from the DLAM deep learning model for predicting essential proteins. The dataset was created by Shunxian Zhou and last updated on April 14, 2026. It presents model performance metrics from evaluations on the DIP and BioGRID protein interaction datasets.
DLAM is a deep learning framework for predicting essential proteins, integrating domain composition, subcellular localization, orthology, gene expression, and a weighted protein-protein interaction network. The dataset contains model performance results on the DIP and BioGRID datasets, achieving strong discrimination and ranking metrics. It was authored by Shunxian Zhou and last updated on April 14, 2026.
DLAM is a deep learning model that predicts protein essentiality by integrating four biological cues and a weighted protein-protein interaction network. The 2.7 MB Excel file contains results from evaluations on the DIP and BioGRID datasets, showing strong performance metrics like ROC-AUC and AP. Authored by Shunxian Zhou and last updated in April 2026, it is shared under a CC-BY-4.0 license.
Renewed companies in the municipality of Guadalajara de Buga for the year 2025. The dataset includes columns for financial metrics like net utility and assets, demographic information such as gender and birth date, and company identifiers. It was published on the Socrata platform via datos.gov.co and last updated on May 18, 2026.
Experimental data supporting a paper on collective emission from subwavelength atom-like emitter arrays in the presence of inhomogeneous broadening. The dataset is 37.1 KB in size and was authored by Uri Israeli. It was last updated on May 28, 2026.
England's regulated waste management facilities, around 6,000 sites, report quantities and types of waste received and sent on. The Environment Agency provides this calendar year 2013 data in interrogatable formats for compliance monitoring and planning. Operator returns are public unless commercial confidentiality is claimed, in which case site details are withheld.
Environment Agency's Waste Data Interrogator 2012 contains annual waste quantity and type data from around 6,000 regulated waste management facilities in the UK. Operators report waste received on-site and waste sent onward, supporting compliance monitoring and planning for new facilities. The dataset has been provided in an interrogatable format since 2006, though site details are withheld for operators claiming commercial confidentiality.
The Environment Agency collects annual data from around 6,000 regulated waste management facilities in the UK. This dataset details quantities and types of waste received and sent on from sites, used for compliance monitoring and planning. Data has been provided in an interrogatable format since 2006, though site details are omitted where commercial confidentiality is claimed.
Around 6,000 regulated UK waste management facilities report annual data on waste received and transferred since 2006. The Environment Agency uses this data to monitor compliance and assist in planning for new facilities, with some site details withheld for commercial confidentiality. Data is public register information, aggregated for national and local authority use.