1. Detect Malacious Executable(AntiVirus): I extract features from malacious and non-malacious and create and training dataset to teach svm classifier.Dataset made of unknown executable to detect if it is virus or normal safe executable.
2. DrivFace: The DrivFace contains images sequences of subjects while driving in real scenarios. It is composed of 606 samples of 640×480, acquired over different days from 4 drivers with several facial features.
3. Gas sensor array exposed to turbulent gas mixtures: A chemical detection platform composed of 8 chemoresistive gas sensors was exposed to turbulent gas mixtures generated naturally in a wind tunnel. The acquired time series of the sensors are provided.
4. NoisyOffice: Corpus intended to do cleaning (or binarization) and enhancement of noisy grayscale printed text images using supervised learning methods. Noisy images and their corresponding ground truth provided.
5. Northix: Northix is designed to be a schema matching benchmark problem for data integration of two entity relationship databases.
6. Parkinson's Disease Classification: The data used in this study were gathered from 188 patients with PD (107 men and 81 women) with ages ranging from 33 to 87 (65.1±10.9).
7. PEMS-SF: 15 months worth of daily data (440 daily records) that describes the occupancy rate, between 0 and 1, of different car lanes of the San Francisco bay area freeways across time.
8. Twin gas sensor arrays: 5 replicates of an 8-MOX gas sensor array were exposed to different gas conditions (4 volatiles at 10 concentration levels each).
9. Ultrasonic flowmeter diagnostics: Fault diagnosis of four liquid ultrasonic flowmeters