1. 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.
2. 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
3. Robot Execution Failures: This dataset contains force and torque measurements on a robot after failure detection. Each failure is characterized by 15 force/torque samples collected at regular time intervals
4. Demospongiae: Marine sponges of the Demospongiae class classification domain.
5. Thoracic Surgery Data: The data is dedicated to classification problem related to the post-operative life expectancy in the lung cancer patients: class 1 - death within one year after surgery, class 2 - survival.
6. Low Resolution Spectrometer: From IRAS data -- NASA Ames Research Center
7. ILPD (Indian Liver Patient Dataset): This data set contains 10 variables that are age, gender, total Bilirubin, direct Bilirubin, total proteins, albumin, A/G ratio, SGPT, SGOT and Alkphos.
8. Northix: Northix is designed to be a schema matching benchmark problem for data integration of two entity relationship databases.
9. ser Knowledge Modeling Data (Students' Knowledge Levels on DC Electrical Machines): The dataset is about the users' learning activities and knowledge levels on subjects of DC Electrical Machines. The dataset had been obtained from online web-courses and reported in my Ph.D. Thesis.
10. 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.
11. 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.
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. Fertility: 100 volunteers provide a semen sample analyzed according to the WHO 2010 criteria. Sperm concentration are related to socio-demographic data, environmental factors, health status, and life habits