1. Amazon Commerce reviews set: The dataset is used for authorship identification in online Writeprint which is a new research field of pattern recognition.
2. APS Failure at Scania Trucks: The datasets' positive class consists of component failures for a specific component of the APS system. The negative class consists of trucks with failures for components not related to the APS.
3. DeliciousMIL: A Data Set for Multi-Label Multi-Instance Learning with Instance Labels: This dataset includes 1) 12234 documents (8251 training, 3983 test) extracted from DeliciousT140 dataset, 2) class labels for all documents, 3) labels for a subset of sentences of the test documents.
4. Dynamic Features of VirusShare Executables: This dataset contains the dynamic features of 107,888 executables, collected by VirusShare from Nov/2010 to Jul/2014.
5. Gas sensor arrays in open sampling settings: The dataset contains 18000 time-series recordings from a chemical detection platform at six different locations in a wind tunnel facility in response to ten high-priority chemical gaseous substances
6. Gastrointestinal Lesions in Regular Colonoscopy: This dataset contains features extracted from colonoscopy videos used to detect gastrointestinal lesions. It contains 76 lesions: 15 serrated adenomas, 21 hyperplastic lesions and 40 adenoma.
7. Hill-Valley: Each record represents 100 points on a two-dimensional graph. When plotted in order (from 1 through 100) as the Y co-ordinate, the points will create either a Hill (a “bump” in the terrain) or a Valley (a “dip” in the terrain).
8. Low Resolution Spectrometer: From IRAS data -- NASA Ames Research Center
9. NoisyOffice: Corpus intended to do cleaning (or binarization) and enhancement of noisy grayscale printed text images using supervised learning methods. Noisy images and their corresponding ground truth provided.
10. Northix: Northix is designed to be a schema matching benchmark problem for data integration of two entity relationship databases.
11. Simulated Falls and Daily Living Activities Data Set: 20 falls and 16 daily living activities were performed by 17 volunteers with 5 repetitions while wearing 6 sensors (3.060 instances) that attached to their head, chest, waist, wrist, thigh and ankle.