1. Musk (Version 1): The goal is to learn to predict whether new molecules will be musks or non-musks
2. Low Resolution Spectrometer: From IRAS data -- NASA Ames Research Center
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. Connectionist Bench (Sonar, Mines vs. Rocks): The task is to train a network to discriminate between sonar signals bounced off a metal cylinder and those bounced off a roughly cylindrical rock.
5. Ionosphere: Classification of radar returns from the ionosphere
6. Climate Model Simulation Crashes: Given Latin hypercube samples of 18 climate model input parameter values, predict climate model simulation crashes and determine the parameter value combinations that cause the failures.
7. Wine: Using chemical analysis determine the origin of wines
8. Glass Identification: From USA Forensic Science Service; 6 types of glass; defined in terms of their oxide content (i.e. Na, Fe, K, etc)
9. Intelligent Media Accelerometer and Gyroscope (IM-AccGyro) Dataset: The IM-AccGyro dataset is devised to benchmark techniques dealing with human activity recognition based on inertial sensors.