1. 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.
2. banknote authentication: Data were extracted from images that were taken for the evaluation of an authentication procedure for banknotes.
3. 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
4. Ecoli: This data contains protein localization sites
5. StoneFlakes: Stone flakes are waste products of the stone tool production in
the prehistoric era. The variables are means of geometric and
stylistic features of the flakes contained in different inventories.
6. Iris: Famous database; from Fisher, 1936
7. 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.
8. Indoor User Movement Prediction from RSS data: This dataset contains temporal data from a Wireless Sensor Network deployed in real-world office environments. The task is intended as real-life benchmark in the area of Ambient Assisted Living.
9. Occupancy Detection : Experimental data used for binary classification (room occupancy) from Temperature,Humidity,Light and CO2. Ground-truth occupancy was obtained from time stamped pictures that were taken every minute.
10. Improved Spiral Test Using Digitized Graphics Tablet for Monitoring Parkinson’s Disease: Handwriting database consists of 25 PWP(People with Parkinson) and 15 healthy individuals.Three types of recordings (Static Spiral Test, Dynamic Spiral Test and Stability Test) are taken.
11. Yeast: Predicting the Cellular Localization Sites of Proteins
12. Blood Transfusion Service Center: Data taken from the Blood Transfusion Service Center in Hsin-Chu City in Taiwan -- this is a classification problem.
13. Vertebral Column: Data set containing values for six biomechanical features used to classify orthopaedic patients into 3 classes (normal, disk hernia or spondilolysthesis) or 2 classes (normal or abnormal).
14. seeds: Measurements of geometrical properties of kernels belonging to three different varieties of wheat. A soft X-ray technique and GRAINS package were used to construct all seven, real-valued attributes.
15. Daphnet Freezing of Gait: This dataset contains the annotated readings of 3 acceleration sensors at the hip and leg of Parkinson's disease patients that experience freezing of gait (FoG) during walking tasks.
16. ISTANBUL STOCK EXCHANGE: Data sets includes returns of Istanbul Stock Exchange with seven other international index; SP, DAX, FTSE, NIKKEI, BOVESPA, MSCE_EU, MSCI_EM from Jun 5, 2009 to Feb 22, 2011.
17. Pima Indians Diabetes: From National Institute of Diabetes and Digestive and Kidney Diseases; Includes cost data (donated by Peter Turney)
18. Online Retail: This is a transnational data set which contains all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail.
19. Energy efficiency: This study looked into assessing the heating load and cooling load requirements of buildings (that is, energy efficiency) as a function of building parameters.
20. User Knowledge Modeling: It is the real dataset about the students' knowledge status about the subject of Electrical DC Machines. The dataset had been obtained from Ph.D. Thesis.
21. Wholesale customers: The data set refers to clients of a wholesale distributor. It includes the annual spending in monetary units (m.u.) on diverse product categories
22. Haberman's Survival: Dataset contains cases from study conducted on the survival of patients who had undergone surgery for breast cancer
23. Statlog (Shuttle): The shuttle dataset contains 9 attributes all of which are numerical. Approximately 80% of the data belongs to class 1
24. Mammographic Mass: Discrimination of benign and malignant mammographic masses based on BI-RADS attributes and the patient's age.