1. Bach Chorales: Time-series data based on chorales; challenge is to learn generative grammar; data in Lisp
2. ICMLA 2014 Accepted Papers Data Set: This data set compromises the metadata for the 2014 ICMLA conference's accepted papers, including ID, paper titles, author's keywords, abstracts and sessions in which they were exposed.
3. Pittsburgh Bridges: Bridges database that has original and numeric-discretized datasets
4. Tennis Major Tournament Match Statistics: This is a collection of 8 files containing the match statistics for both women and men at the four major tennis tournaments of the year 2013. Each file has 42 columns and a minimum of 76 rows.
5. Teaching Assistant Evaluation: The data consist of evaluations of teaching performance; scores are "low", "medium", or "high"
6. Flags: From Collins Gem Guide to Flags, 1986
7. Automobile: From 1985 Ward's Automotive Yearbook
8. BuddyMove Data Set: User interest information extracted from user reviews published in holidayiq.com about various types of point of interests in South India
9. University: Data in original (LISP-readable) form
10. Badges: Badges labeled with a "+" or "-" as a function of a person's name
11. 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.
12. Libras Movement: The data set contains 15 classes of 24 instances each. Each class references to a hand movement type in LIBRAS (Portuguese
name 'LÍngua BRAsileira de Sinais', oficial brazilian signal language).
13. Auto MPG: Revised from CMU StatLib library, data concerns city-cycle fuel consumption
14. 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.
15. MONK's Problems: A set of three artificial domains over the same attribute space; Used to test a wide range of induction algorithms
16. Meta-data: Meta-Data was used in order to give advice about which classification method is appropriate for a particular dataset (taken from results of Statlog project).
17. 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.
18. Synthetic Control Chart Time Series: This data consists of synthetically generated control charts.
19. 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).
20. Folio: 20 photos of leaves for each of 32 different species.
21. 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
22. Japanese Vowels: This dataset records 640 time series of 12 LPC cepstrum coefficients taken from nine male speakers.
23. Audit Data: Exhaustive one year non-confidential data in the year 2015 to 2016 of firms is collected from the Auditor Office of India to build a predictor for classifying suspicious firms.
24. Statlog (Vehicle Silhouettes): 3D objects within a 2D image by application of an ensemble of shape feature extractors to the 2D silhouettes of the objects.
25. Travel Reviews: Reviews on destinations in 10 categories mentioned across East Asia. Each traveler rating is mapped as Excellent(4), Very Good(3), Average(2), Poor(1), and Terrible(0) and average rating is used.