A small classic dataset from Fisher, 1936. One of the earliest datasets used for evaluation of classification methodologies.
Images of 13,611 grains of 7 different registered dry beans were taken with a high-resolution camera. A total of 16 features; 12 dimensions and 4 shape forms, were obtained from the grains.
Predict whether income exceeds $50K/yr based on census data. Also known as "Census Income" dataset.
A total of 3810 rice grain's images were taken for the two species, processed and feature inferences were made. 7 morphological features were obtained for each grain of rice.
From a metro train in an operational context, readings from pressure, temperature, motor current, and air intake valves were collected from a compressor's Air Production Unit (APU). This dataset reveals real predictive maintenance challenges encountered in the industry. It can be used for failure predictions, anomaly explanations, and other tasks.
The Human Activity Recognition 70+ (HAR70+) dataset is a professionally-annotated dataset containing 18 fit-to-frail older-adult subjects (70-95 years old) wearing two 3-axial accelerometers for around 40 minutes during a semi-structured free-living protocol. The sensors were attached to the right thigh and lower back.
The Human Activity Recognition Trondheim (HARTH) dataset is a professionally-annotated dataset containing 22 subjects wearing two 3-axial accelerometers for around 2 hours in a free-living setting. The sensors were attached to the right thigh and lower back. The professional recordings and annotations provide a promising benchmark dataset for researchers to develop innovative machine learning approaches for precise HAR in free living.
DeFungi is a dataset for direct mycological examination of microscopic fungi images. The images are from superficial fungal infections caused by yeasts, moulds, or dermatophyte fungi. The images have been manually labelled into five classes and curated with a subject matter expert assistance. The images have been cropped with automated algorithms to produce the final dataset.
This dataset contains synthetic aperture radar (SAR) raster imagery for various flood events acquired from the European Space Agencys Sentinel-1A and Sentinel-1B missions, providing C-Band dual-polarized imagery that spans geographical areas of interest in the United States and Bangladesh. The main emphasis was on the labeling of open water areas where specular reflection of the radar signal off of the relatively still, flat open water surface results in reduced backscatter, low amplitude, and an overall darkened appearance within the image. The labels for the water surface reflectance are also provided in GeoTiff rasterized file format in scenes aligned with the SAR source raster imagery.
This dataset contains Turkish comments made by customers on products (computer, tea machine, head phones, modem, parfume, mobile phone, TV, usb)sold on a website. This dataset created by Asst. Prof. Dr. Ekin Ekinci and Prof. Sevinç İlhan Omurca. Please refer to the study "An alternative word embedding approach for knowledge representation in online consumers’ reviews" when using this dataset.