1. Early stage diabetes risk prediction dataset.: This dataset
contains the sign and symptpom data of newly diabetic or would be diabetic patient.
2. Dresses_Attribute_Sales: This dataset contain Attributes of dresses and their recommendations according to their sales.Sales are monitor on the basis of alternate days.
3. : Simulated Data set of Iraqi tourism places: Simulated Data set of Iraqi tourism places with their position (longitude,latitude)and type of interest for each place
4. Student Performance on an entrance examination: This dataset contains data of the candidates who qualified the medical entrance examination for admission to medical colleges of Assam of a particular year and collected by Prof. Jiten Hazarika.
5. Forest type mapping: Multi-temporal remote sensing data of a forested area in Japan. The goal is to map different forest types using spectral data.
6. Folio: 20 photos of leaves for each of 32 different species.
7. Student Academics Performance: The dataset tried to find the end semester percentage prediction based on different social, economic and academic attributes.
8. Kinship: Relational dataset
9. University: Data in original (LISP-readable) form
10. Heart Disease: 4 databases: Cleveland, Hungary, Switzerland, and the VA Long Beach
11. 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
12. Paper Reviews: This sentiment analysis data set contains scientific paper reviews from an international conference on computing and informatics. The task is to predict the orientation or the evaluation of a review.
13. Autistic Spectrum Disorder Screening Data for Children : Children screening data for autism suitable for classification and predictive tasks
14. Autistic Spectrum Disorder Screening Data for Adolescent : Autistic Spectrum Disorder Screening Data for Adolescent. This dataset is related to classification and predictive tasks.
15. CSM (Conventional and Social Media Movies) Dataset 2014 and 2015: 12 features categorized as conventional and social media features. Both conventional features, collected from movies databases on Web as well as social media features(YouTube,Twitter).
16. Autism Screening Adult: Autistic Spectrum Disorder Screening Data for Adult. This dataset is related to classification and predictive tasks.
17. Abscisic Acid Signaling Network: The objective is to determine the set of boolean rules that describe the interactions of the nodes within this plant signaling network. The dataset includes 300 separate boolean pseudodynamic simulations using an asynchronous update scheme.
18. Thoracic Surgery Data: The data is dedicated to classification problem related to the post-operative life expectancy in the lung cancer patients: class 1 - death within one year after surgery, class 2 - survival.
19. ILPD (Indian Liver Patient Dataset): This data set contains 10 variables that are age, gender, total Bilirubin, direct Bilirubin, total proteins, albumin, A/G ratio, SGPT, SGOT and Alkphos.
20. Behavior of the urban traffic of the city of Sao Paulo in Brazil: The database was created with records of behavior of the urban traffic of the city of Sao Paulo in Brazil.
21. Chronic_Kidney_Disease: This dataset can be used to predict the chronic kidney disease and it can be collected from the hospital nearly 2 months of period.
22. Wheat kernels: Measurements of morphological descriptors of wheat kernels from Punjab State. A machine Learning based technique was used to extract 15 features, all are real valued attributes
23. GPS Trajectories: The dataset has been feed by Android app called Go!Track. It is available at Goolge Play Store(https://play.google.com/store/apps/details?id=com.go.router).
24. Connectionist Bench (Vowel Recognition - Deterding Data): Speaker independent recognition of the eleven steady state vowels of British English using a specified training set of lpc derived log area ratios.
25. Fertility: 100 volunteers provide a semen sample analyzed according to the WHO 2010 criteria. Sperm concentration are related to socio-demographic data, environmental factors, health status, and life habits