1. Demand Forecasting for a store: Contains data for a store from week 1 to week 146.
2. Bag of Words: This data set contains five text collections in the form of bags-of-words.
3. Dexter: DEXTER is a text classification problem in a bag-of-word representation. This is a two-class classification problem with sparse continuous input variables. This dataset is one of five datasets of the NIPS 2003 feature selection challenge.
4. 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.
5. Metro Interstate Traffic Volume: Hourly Minneapolis-St Paul, MN traffic volume for westbound I-94. Includes weather and holiday features from 2012-2018.
6. 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.
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. 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.
9. Crop mapping using fused optical-radar data set: Combining optical and PolSAR remote sensing images offers a complementary data set with a significant number of temporal, spectral, textural, and polarimetric features for cropland classification.
10. 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.
11. Image Segmentation: Image data described by high-level numeric-valued attributes, 7 classes
12. Geographical Original of Music: Instances in this dataset contain audio features extracted from 1059 wave files. The task associated with the data is to predict the geographical origin of music.
13. 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
14. 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
15. Air quality: Contains the responses of a gas multisensor device deployed on the field in an Italian city.
16. 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.
17. Madelon: MADELON is an artificial dataset, which was part of the NIPS 2003 feature selection challenge. This is a two-class classification problem with continuous input variables. The difficulty is that the problem is multivariate and highly non-linear.
18. Spoken Arabic Digit: This dataset contains timeseries of mel-frequency cepstrum coefficients (MFCCs) corresponding to spoken Arabic digits. Includes data from 44 male and 44 female native Arabic speakers.
19. 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.
20. 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.
21. 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.