1. EEG Eye State: The data set consists of 14 EEG values and a value indicating the eye state.
2. Molecular Biology (Promoter Gene Sequences): E. Coli promoter gene sequences (DNA) with partial domain theory
3. Molecular Biology (Protein Secondary Structure): From CMU connectionist bench repository; Classifies secondary structure of certain globular proteins
4. Molecular Biology (Splice-junction Gene Sequences): Primate splice-junction gene sequences (DNA) with associated imperfect domain theory
5. Anticancer peptides: Peptides with experimental annotations on their anticancer action on breast and lung cancer cells.
6. Activity recognition with healthy older people using a batteryless wearable sensor: Sequential motion data from 14 healthy older people aged 66 to 86 years old using a batteryless, wearable sensor on top of their clothing for the recognition of activities in clinical environments.
7. chipseq: ChIP-seq experiments characterize protein modifications or binding at
specific genomic locations in specific samples. The machine learning
problem in these data is structured binary classification.
8. Localization Data for Person Activity: Data contains recordings of five people performing different activities. Each person wore four sensors (tags) while performing the same scenario five times.
9. 9mers from cullpdb: Provide a short description of your data set (less than 200 characters).