1. Activity recognition using wearable physiological measurements: This dataset contains features from Electrocardiogram (ECG), Thoracic Electrical Bioimpedance (TEB) and the Electrodermal Activity (EDA) for activity recognition.
2. 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.
3. Anuran Calls (MFCCs): Acoustic features extracted from syllables of anuran (frogs) calls, including the family, the genus, and the species labels (multilabel).
4. Bar Crawl: Detecting Heavy Drinking: Accelerometer and transdermal alcohol content data from a college bar crawl. Used to predict heavy drinking episodes via mobile data.
5. Bar Crawl: Detecting Heavy Drinking: Accelerometer and transdermal alcohol content data from a college bar crawl. Used to predict heavy drinking episodes via mobile data.
6. Cardiotocography: The dataset consists of measurements of fetal heart rate (FHR) and uterine contraction (UC) features on cardiotocograms classified by expert obstetricians.
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. Cuff-Less Blood Pressure Estimation: This Data set provides preprocessed and cleaned vital signals which can be used in designing algorithms for cuff-less estimation of the blood pressure.
9. Diabetes 130-US hospitals for years 1999-2008: This data has been prepared to analyze factors related to readmission as well as other
outcomes pertaining to patients with diabetes.
10. Diabetic Retinopathy Debrecen Data Set: This dataset contains features extracted from the Messidor image set to predict whether an image contains signs of diabetic retinopathy or not.
11. Dorothea: DOROTHEA is a drug discovery dataset. Chemical compounds represented by structural molecular features must be classified as active (binding to thrombin) or inactive. This is one of 5 datasets of the NIPS 2003 feature selection challenge.
12. Drug Review Dataset (Drugs.com): The dataset provides patient reviews on specific drugs along with related conditions and a 10 star patient rating reflecting overall patient satisfaction.
13. EEG Eye State: The data set consists of 14 EEG values and a value indicating the eye state.
14. EEG Steady-State Visual Evoked Potential Signals: This database consists on 30 subjects performing Brain Computer Interface for Steady State Visual Evoked Potentials (BCI-SSVEP).
15. EMG data for gestures: These are files of raw EMG data recorded by MYO Thalmic bracelet
16. Epileptic Seizure Recognition: This dataset is a pre-processed and re-structured/reshaped version of a very commonly used dataset featuring epileptic seizure detection.
17. Estimation of obesity levels based on eating habits and physical condition : This dataset include data for the estimation of obesity levels in individuals from the countries of Mexico, Peru and Colombia, based on their eating habits and physical condition.
18. Hepatitis C Virus (HCV) for Egyptian patients: Egyptian patients who underwent treatment dosages for HCV about 18 months. Discretization should be applied based on expert recommendations; there is an attached file shows how.
19. KASANDR: KASANDR is a novel, publicly available collection for recommendation systems that records the behavior of customers of the European leader in e-Commerce advertising, Kelkoo.
20. KEGG Metabolic Reaction Network (Undirected): KEGG Metabolic pathways modeled as un-directed reaction network. Variety of graphical features presented.
21. KEGG Metabolic Relation Network (Directed): KEGG Metabolic pathways modeled as directed relation network. Variety of graphical features presented.
22. 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.
23. Mice Protein Expression: Expression levels of 77 proteins measured in the cerebral cortex of 8 classes of control and Down syndrome mice exposed to context fear conditioning, a task used to assess associative learning.
24. One-hundred plant species leaves data set: Sixteen samples of leaf each of one-hundred plant species. For each sample, a shape descriptor, fine scale margin and texture histogram are given.
25. p53 Mutants: The goal is to model mutant p53 transcriptional activity (active vs inactive) based on data extracted from biophysical simulations.
26. Parkinson Speech Dataset with Multiple Types of Sound Recordings: The training data belongs to 20 Parkinson's Disease (PD) patients and 20 healthy subjects. From all subjects, multiple types of sound recordings (26) are taken.
27. Parkinsons Telemonitoring: Oxford Parkinson's Disease Telemonitoring Dataset
28. Physicochemical Properties of Protein Tertiary Structure: This is a data set of Physicochemical Properties of Protein Tertiary Structure. The data set is taken from CASP 5-9. There are 45730 decoys and size varying from 0 to 21 armstrong.
29. QSAR fish bioconcentration factor (BCF): Experimental bioconcentration factor (BCF) for 1056 molecules and binary fingeprints (extended connectivity) to be used for QSAR modeling.
30. Reuters RCV1 RCV2 Multilingual, Multiview Text Categorization Test collection: This test collection contains feature characteristics of documents originally written in five different languages and their translations, over a common set of 6 categories.
31. sEMG for Basic Hand movements: The sEMG for Basic Hand movements includes 2 databases of surface electromyographic signals of 6 hand movements using Delsys' EMG System. Healthy subjects conducted six daily life grasps.
32. Simulated Falls and Daily Living Activities Data Set: 20 falls and 16 daily living activities were performed by 17 volunteers with 5 repetitions while wearing 6 sensors (3.060 instances) that attached to their head, chest, waist, wrist, thigh and ankle.
33. Smartphone-Based Recognition of Human Activities and Postural Transitions: Activity recognition data set built from the recordings of 30 subjects performing basic activities and postural transitions while carrying a waist-mounted smartphone with embedded inertial sensors.
34. Tamilnadu Electricity Board Hourly Readings: This data can be effectively produced the result to fewer parameter of the Load profile can be reduced in the Database
35. Yeast: Predicting the Cellular Localization Sites of Proteins