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General ML benchmarks, tabular data, AutoML, recommendation systems, anomaly detection, evaluation suites
165,125 datasets
A gene panel dataset derived from RNA-seq analysis to identify sex-specific biomarkers for bladder cancer. The data was generated by Joseph R. Pizzi using machine learning feature selection methods and last updated in April 2026. Male and female-specific gene panels achieved areas under the ROC curve of 0.932 and 0.914, respectively, in distinguishing cancer from non-tumor samples.
A dataset by Joseph R. Pizzi, last updated on 2026-04-29, containing gene panels identified through machine learning for sex-specific bladder cancer. The data likely includes gene identifiers and associated metrics from an analysis of gender and disease-stratified RNA-seq data. The male and female-specific panels achieved areas under the ROC curve of 0.932 and 0.914, respectively, in distinguishing cancer from non-tumor controls.
A gene panel dataset created by Joseph R. Pizzi and last updated in April 2026. It contains machine learning-identified biomarkers for sex-specific bladder cancer development and progression, derived from gender and disease-stratified RNA-seq data. The male and female-specific panels achieved areas under the ROC curve of 0.932 and 0.914, respectively, in distinguishing cancer from non-tumor controls.
Data Sheet 8_Machine learning-based determination of sex-related bladder cancer biomarkers.csv contains gene panels identified through machine learning analysis of gender-stratified RNA-seq data. The dataset was created by Joseph R. Pizzi and last updated on 2026-04-29. It includes results from four feature selection methods, with male and female-specific gene panels achieving areas under the ROC curve of 0.932 and 0.914, respectively.
Data Sheet 10 contains gene panels identified as potential sex-specific biomarkers for bladder cancer. The dataset was created by Joseph R. Pizzi and last updated on 2026-04-29. It is a small CSV file (15.0 KB) resulting from a machine learning analysis of gender and disease-stratified RNA-seq data.
A gene panel dataset from a machine learning study on sex-specific bladder cancer biomarkers. The data includes male and female-specific gene panels derived from RNA-seq data using four feature selection methods, achieving areas under the ROC curve of 0.932 and 0.914, respectively. The dataset was created by Joseph R. Pizzi and last updated on 2026-04-29.
Global ESG conflict risk assessment for critical energy transition minerals, created by Xiaoyang Lin and last updated in May 2026. The 4.3 MB dataset includes spatial training data, preprocessing and machine learning code, and final risk results categorized by mineral type and region.
Australian spectral data from the Coringa Herald region in 2006, hosted in the National Spectral Database. The dataset is part of a CSIRO research project on remote sensing for marine protected areas, with related publications from 2010 and 2013. It is managed by the Australian Ocean Data Network.
Temperature loggers deployed at Helix Reef collected this sea water data from 21 April 2012 to 04 May 2026. The Australian Ocean Data Network is the listed organization for the dataset. It was last updated on the platform in June 2026.
Legacy product from the Australian Ocean Data Network with no abstract available. The dataset likely contains geochemical measurements from a research cruise investigating phosphorite formation mechanisms in the ocean off northern New South Wales, Australia. It was last updated on 2026-06-27 21:45:33.161747.
Eastern Indian Ocean sediment data from the Mesozoic and Cenozoic eras, published by the Australian Ocean Data Network. The dataset is a legacy product with no abstract available, and its last update is recorded as 2026-06-27. File formats include HTML and PDF documents.
Since 2013, this dataset contains the historical tuition fee values implemented by the Institución Universitaria Colegio Mayor del Cauca. The data is structured by academic program and year, with columns for value, concept, program name, and year. It is published via the Socrata platform on the Colombian open data portal.
Legacy product from the Australian Ocean Data Network concerning offshore phosphate deposits. The dataset likely contains geospatial and geological information relevant to mineral resource assessment in the southwest Pacific region. It was last updated on 2026-06-27.
Russian oceanographic vessel 'Vitiaz'- techniques and equipment is a dataset published by the Australian Ocean Data Network on data_gov_au. The dataset likely contains information about the techniques and equipment used aboard the Russian research vessel Vitiaz. Metadata is minimal; the actual content and scale require verification after download.
Northwest Australia's Canning region is covered by this dataset of gravity, magnetic, and bathymetry grids derived from levelled data. The dataset is a legacy product published by the Australian Ocean Data Network on the data_gov_au platform. It was last updated on 2026-06-27.
Legacy geophysical data product for the Northwest Shelf of Australia, published by the Australian Ocean Data Network. The dataset includes grids for gravity, magnetic, and bathymetry measurements derived from levelled data. Metadata is minimal, with the last update recorded as 2026-06-27.
AGSO Formats for Marine Navigation Digital Data is a legacy dataset published by the Australian Ocean Data Network. The dataset's abstract and specific content are unavailable, but the title suggests it contains digital data formats related to marine navigation. It was last updated on 2026-06-27.
Legacy data product concerning seabed margins and resource potential for the Macquarie Ridge, Norfolk Ridge, and Lord Howe Rise regions. It was published by the Australian Ocean Data Network on the data_gov_au platform. The record was last updated on 2026-06-27.
Legacy product from the Australian Ocean Data Network with no abstract available. The dataset likely contains information about seabed composition and recent sediment deposits in Milne Bay, Papua New Guinea. It was last updated on 2026-06-27 20:55:48.852249.
Depth and thickness maps for sedimentary sequences under the Exmouth Plateau are hosted by the Australian Ocean Data Network. The dataset is a legacy product, and a detailed abstract is not available. It was last updated on 2026-06-27.