1. Leaf: This dataset consists in a collection of shape and texture features extracted from digital images of leaf specimens originating from a total of 40 different plant species.
2. MHEALTH Dataset: The MHEALTH (Mobile Health) dataset is devised to benchmark techniques dealing with human behavior analysis based on multimodal body sensing.
3. 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
4. Mesothelioma’s disease data set : Mesothelioma’s disease data set were prepared at Dicle University Faculty of Medicine in Turkey.
Three hundred and twenty-four Mesothelioma patient data. In the dataset, all samples have 34 features.
5. Turkish Music Emotion Dataset: There are four different classes of music emotions in the dataset: happy, sad, angry, and relax.
6. 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).
7. 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).
8. Optical Interconnection Network : This dataset contains 640 performance measurements from a simulation of 2-Dimensional Multiprocessor Optical Interconnection Network.
9. 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.