![]() ![]() 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.ġ6. ![]() This dataset is one of five datasets of the NIPS 2003 feature selection challenge.ġ5. This is a two-class classification problem with sparse continuous input variables. Dexter: DEXTER is a text classification problem in a bag-of-word representation. The task associated with the data is to predict how many comments the post will receive.ġ4. Facebook Comment Volume Dataset: Instances in this dataset contain features extracted from facebook posts. It contains 50 attributes divided into two files for each video.ġ3. Gesture Phase Segmentation: The dataset is composed by features extracted from 7 videos with people gesticulating, aiming at studying Gesture Phase Segmentation. Data are collected continuously while residents perform their normal routines.ġ2. Human Activity Recognition from Continuous Ambient Sensor Data: This dataset represents ambient data collected in homes with volunteer residents. ![]() Image Segmentation: Image data described by high-level numeric-valued attributes, 7 classesġ1. The difficulty is that the problem is multivariate and highly non-linear.ġ0. This is a two-class classification problem with continuous input variables. Madelon: MADELON is an artificial dataset, which was part of the NIPS 2003 feature selection challenge. Includes weather and holiday features from 2012-2018.ĩ. Metro Interstate Traffic Volume: Hourly Minneapolis-St Paul, MN traffic volume for westbound I-94. Power consumption of Tetouan city: This dataset is related to power consumption of three different distribution networks of Tetouan city which is located in north Morocco.Ĩ. QSAR biodegradation: Data set containing values for 41 attributes (molecular descriptors) used to classify 1055 chemicals into 2 classes (ready and not ready biodegradable).ħ. The task is to decide from a comparison pattern whether the underlying records belong to one person.Ħ. Record Linkage Comparison Patterns: Element-wise comparison of records with personal data from a record linkage setting. Data come from two of longwalls located in a Polish coal mine.ĥ. seismic-bumps: The data describe the problem of high energy (higher than 10^4 J) seismic bumps forecasting in a coal 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.Ĥ. Google user rating ranges from 1 to 5 and average user rating per category is calculated.ģ. Tarvel Review Ratings: Google reviews on attractions from 24 categories across Europe are considered. Songs are mostly western, commercial tracks ranging from 1922 to 2011, with a peak in the year 2000s.Ģ. YearPredictionMSD: Prediction of the release year of a song from audio features. , 2017.Check out the beta version of the new UCI Machine Learning Repository we are currently testing! Contact us if you have any issues, questions, or concerns. Michaël Defferrard, Kirell Benzi, Pierre Vandergheynst, Xavier Bresson. Mel Frequency Cepstral Coefficient (MFCC), 140 attributes Nine audio features computed across time and summarized with seven statistics (mean, standard deviation, skew, kurtosis, median, minimum, maximum):ģ. * Please see the paper and the GitHub repository for more information ( ) * The dataset is split into four sizes: small, medium, large, full. ![]() * Given the metadata, multiple problems can be explored: recommendation, genre recognition, artist identification, year prediction, music annotation, unsupervized categorization. * Nine audio features (consisting of 518 attributes) for each of the 106,574 tracks. It is on average 10 millions samples per track. * Audio track (encoded as mp3) of each of the 106,574 tracks. Michaël Defferrard, Kirell Benzi, Pierre Vandergheynst, Xavier Bresson, EPFL LTS2. Click here to try out the new site.įMA: A Dataset For Music Analysis Data Setĭownload: Data Folder, Data Set DescriptionĪbstract: FMA features 106,574 tracks and includes song title, album, artist, genres play counts, favorites, comments description, biography, tags together with audio (343 days, 917 GiB) and features. Check out the beta version of the new UCI Machine Learning Repository we are currently testing! Contact us if you have any issues, questions, or concerns. ![]()
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