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1. 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.

2. 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.

3. 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.