1. Air quality: Contains the responses of a gas multisensor device deployed on the field in an Italian city.
2. Bach Chorales: Time-series data based on chorales; challenge is to learn generative grammar; data in Lisp
3. Chronic_Kidney_Disease: This dataset can be used to predict the chronic kidney disease and it can be collected from the hospital nearly 2 months of period.
4. CMU Face Images: This data consists of 640 black and white face images of people taken with varying pose (straight, left, right, up), expression (neutral, happy, sad, angry), eyes (wearing sunglasses or not), and size
5. Connectionist Bench (Vowel Recognition - Deterding Data): Speaker independent recognition of the eleven steady state vowels of British English using a specified training set of lpc derived log area ratios.
6. DGP2 - The Second Data Generation Program: Generates application domains based on specific parameters, number of features, and proportion of positive to negative examples
7. Document Understanding: Five concepts, expressed as predicates, to be learned
8. Entree Chicago Recommendation Data: This data contains a record of user interactions with the Entree Chicago restaurant recommendation system.
9. Firm-Teacher_Clave-Direction_Classification: The data are binary attack-point vectors and their clave-direction class(es) according to the partido-alto-based paradigm.
10. Folio: 20 photos of leaves for each of 32 different species.
11. Geographical Original of Music: Instances in this dataset contain audio features extracted from 1059 wave files. The task associated with the data is to predict the geographical origin of music.
12. 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).
13. Legal Case Reports: A textual corpus of 4000 legal cases for automatic summarization and citation analysis. For each document we collect catchphrases, citations sentences, citation catchphrases and citation classes.
14. NSF Research Award Abstracts 1990-2003: This data set consists of (a) 129,000 abstracts describing NSF awards for basic research, (b) bag-of-word data files extracted from the abstracts, (c) a list of words used for indexing the bag-of-word
15. Prodigy: Assorted domains like blocksworld, eightpuzzle, and schedworld.
16. Pseudo Periodic Synthetic Time Series: This data set is designed for testing indexing schemes in time series databases. The data appears highly periodic, but never exactly repeats itself.
17. Reuters-21578 Text Categorization Collection: This is a collection of documents that appeared on Reuters newswire in 1987. The documents were assembled and indexed with categories.
18. Sentence Classification: Contains sentences from the abstract and introduction of 30 articles annotated with a modified Argumentative Zones annotation scheme. These articles come from biology, machine learning and psychology.
19. Sentiment Labelled Sentences: The dataset contains sentences labelled with positive or negative sentiment.
20. Spoken Arabic Digit: This dataset contains timeseries of mel-frequency cepstrum coefficients (MFCCs) corresponding to spoken Arabic digits. Includes data from 44 male and 44 female native Arabic speakers.
21. Statlog Project: Various Databases: Vehicle silhouttes, Landsat Sattelite, Shuttle, Australian Credit Approval, Heart Disease, Image Segmentation, German Credit
22. Twenty Newsgroups: This data set consists of 20000 messages taken from 20 newsgroups.
23. Undocumented: Various datasets without documentation (feel free to explore!)
24. University: Data in original (LISP-readable) form
25. University of Tehran Question Dataset 2016 (UTQD.2016): Persian questions gathered from a jeopardy game broadcasted on Iranian national television.
26. User Identification From Walking Activity: The dataset collects data from an Android smartphone positioned in the chest pocket from 22 participants walking in the wild over a predefined path.
27. USPTO Algorithm Challenge, run by NASA-Harvard Tournament Lab and TopCoder Problem: Pat: Data used for USPTO Algorithm Competition. Contains drawing pages from US patents with manually labeled figure and part labels.