1. SCADI: First self-care activities dataset based on ICF-CY.
2. Mturk User-Perceived Clusters over Images: This dataset was collected by Shan-Hung Wu and DataLab members at NTHU, Taiwan. There're 325 user-perceived clusters from 100 users and their corresponding descriptions.
3. ElectricityLoadDiagrams20112014: This data set contains electricity consumption of 370 points/clients.
4. A study of Asian Religious and Biblical Texts: Mainly from Project Gutenberg, we combine Upanishads, Yoga Sutras, Buddha Sutras, Tao Te Ching and Book of Wisdom, Book of Proverbs, Book of Ecclesiastes and Book of Ecclesiasticus
5. DrivFace: The DrivFace contains images sequences of subjects while driving in real scenarios. It is composed of 606 samples of 640×480, acquired over different days from 4 drivers with several facial features.
6. gene expression cancer RNA-Seq: This collection of data is part of the RNA-Seq (HiSeq) PANCAN data set, it is a random extraction of gene expressions of patients having different types of tumor: BRCA, KIRC, COAD, LUAD and PRAD.
7. Reuter_50_50: The dataset is used for authorship identification in online Writeprint which is a new research field of pattern recognition.
8. TTC-3600: Benchmark dataset for Turkish text categorization: The TTC-3600 data set is a collection of Turkish news and articles including categorized 3,600 documents from 6 well-known portals in Turkey. It has 4 different forms in ARFF Weka format.
9. MEx: The MEx Multi-modal Exercise dataset contains data of 7 different
physiotherapy exercises, performed by 30 subjects recorded with 2 accelerometers,
a pressure mat and a depth camera.
10. Daily and Sports Activities: The dataset comprises motion sensor data of 19 daily and sports activities each performed by 8 subjects in their own style for 5 minutes. Five Xsens MTx units are used on the torso, arms, and legs.
11. Human Activity Recognition Using Smartphones: Human Activity Recognition database built from the recordings of 30 subjects performing activities of daily living (ADL) while carrying a waist-mounted smartphone with embedded inertial sensors.
12. NIPS Conference Papers 1987-2015: This data set contains the distribution of words in the full text of the NIPS conference papers published from 1987 to 2015.
13. Epileptic Seizure Recognition: This dataset is a pre-processed and re-structured/reshaped version of a very commonly used dataset featuring epileptic seizure detection.
14. Gas Sensor Array Drift Dataset at Different Concentrations: This archive contains 13910 measurements from 16 chemical sensors exposed to 6 different gases at various concentration levels.
15. Amazon Access Samples: Amazon's InfoSec is getting smarter about the way Access data is leveraged. This is an anonymized sample of access provisioned within the company.
16. Health News in Twitter: The data was collected in 2015 using Twitter API. This dataset contains health news from more than 15 major health news agencies such as BBC, CNN, and NYT.
17. FMA: A Dataset For Music Analysis: FMA features 106,574 tracks and includes song title, album, artist, genres; play counts, favorites, comments; description, biography, tags; together with audio (343 days, 917 GiB) and features.
18. YouTube Multiview Video Games Dataset: This dataset contains about 120k instances, each described by 13 feature types, with class information, specially useful for exploring multiview topics (cotraining, ensembles, clustering,..).
19. Repeat Consumption Matrices: The dataset contains 7 datasets of User - Item matrices, where each entry represents how many times a user consumed an item. Item is used as an umbrella term for various categories.
20. detection_of_IoT_botnet_attacks_N_BaIoT: This dataset addresses the lack of public botnet datasets, especially for the IoT. It suggests *real* traffic data, gathered from 9 commercial IoT devices authentically infected by Mirai and BASHLITE.
21. Bag of Words: This data set contains five text collections in the form of bags-of-words.
22. Kitsune Network Attack Dataset: A cybersecurity dataset containing nine different network attacks on a commercial IP-based surveillance system and an IoT network. The dataset includes reconnaissance, MitM, DoS, and botnet attacks.