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12 Data Sets

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1. Australian Sign Language signs (High Quality): This data consists of sample of Auslan (Australian Sign Language) signs. 27 examples of each of 95 Auslan signs were captured from a native signer using high-quality position trackers

2. Corel Image Features: This dataset contains image features extracted from a Corel image collection. Four sets of features are available based on the color histogram, color histogram layout, color moments, and co-occurence

3. Facebook Comment Volume Dataset: Instances in this dataset contain features extracted from facebook posts. The task associated with the data is to predict how many comments the post will receive.

4. Gesture Phase Segmentation: The dataset is composed by features extracted from 7 videos with people gesticulating, aiming at studying Gesture Phase Segmentation. It contains 50 attributes divided into two files for each video.

5. Human Activity Recognition from Continuous Ambient Sensor Data: This dataset represents ambient data collected in homes with volunteer residents. Data are collected continuously while residents perform their normal routines.

6. Image Segmentation: Image data described by high-level numeric-valued attributes, 7 classes

7. QSAR biodegradation: Data set containing values for 41 attributes (molecular descriptors) used to classify 1055 chemicals into 2 classes (ready and not ready biodegradable).

8. Record Linkage Comparison Patterns: Element-wise comparison of records with personal data from a record linkage setting. The task is to decide from a comparison pattern whether the underlying records belong to one person.

9. seismic-bumps: The data describe the problem of high energy (higher than 10^4 J) seismic bumps forecasting in a coal mine. Data come from two of longwalls located in a Polish coal mine.

10. Statlog (Image Segmentation): This dataset is an image segmentation database similar to a database already present in the repository (Image segmentation database) but in a slightly different form.

11. Tarvel Review Ratings: Google reviews on attractions from 24 categories across Europe are considered. Google user rating ranges from 1 to 5 and average user rating per category is calculated.

12. YearPredictionMSD: Prediction of the release year of a song from audio features. Songs are mostly western, commercial tracks ranging from 1922 to 2011, with a peak in the year 2000s.


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