19,997 machine learning datasets
19,997 dataset results
Fire Drill Anti-Pattern Dataset is a collection of nine real-world software projects for detection of the fire drill anti-pattern with ground truth, issue-tracking data, source code density, models and code. The data is supposed to aid the detection of the presence of the Fire Drill anti-pattern. It includes data, ground truth, code, and notebooks. The data supports two distinct methods of detecting the AP: a) through issue-tracking data, and b) through the underlying source code. Therefore, this package includes the following:
OpenWPM Crawls is a dataset of 103 online, mostly mainstream news websites. With the help of two experts, alongside data from the Media Ownership Monitor of the Reporters without Borders, we label these websites according to their partisanship (Left, Right, or Centre). We study and compare user tracking on these sites with different metrics: numbers of cookies, cookie synchronizations, device fingerprinting, and invisible pixel-based tracking. We find that Left and Centre websites serve more cookies than Right-leaning websites. However, through cookie synchronization, more user IDs are synchronized in Left websites than Right or Centre. Canvas fingerprinting is used similarly by Left and Right, and less by Centre. Invisible pixel-based tracking is 50% more intense in Centre-leaning websites than Right, and 25% more than Left. Desktop versions of news websites deliver more cookies than their mobile counterparts. A handful of third-parties are tracking users in most websites in this stud
BLM-17m is a labeled dataset for topic detection that contains 17 million tweets. These Tweets are collected from 25 May 2020 to 21 August 2020 that covers 89 days from start of the George Floy incident. The dataset was labelled by monitoring most trending news topics from global and local newspapers.
NAVVS is a volumetric dataset of naturalistic actions whose captured sound and visual appearance yield an open-access resource for immersive and interactive research within an artificial 3D audio-visual environment, such as VR/AR/XR with six degree-of-freedom (6DoF) interaction. It includes a variety of short volumetric sounding actions. It provides a valuable resource for multimodal research and testing under realistic conditions. The dataset includes ten different actions designed with both semantic and acoustic diversity. For each action, four 2-seconds takes are available to provide a total of forty audio-visual clips.
This is a benchmark dataset for mid-price forecasting of limit order book data. It is a dataset of high-frequency limit order markets for mid-price prediction. The authors extracted normalized data representations of time series data for five stocks from the NASDAQ Nordic stock market for a time period of ten consecutive days, leading to a dataset of ~4,000,000 time series samples in total. A day-based anchored cross-validation experimental protocol is also provided that can be used as a benchmark for comparing the performance of state-of-the-art methodologies.
Analytic provenance is a data repository that can be used to study human analysis activity, thought processes, and software interaction with visual analysis tools during exploratory data analysis. It was collected during a series of user studies involving exploratory data analysis scenario with textual and cyber security data. Interactions logs, think-alouds, videos and all coded data in this study are available online for research purposes.
CSI is a criminal conversational dataset for speaker identification built from the CSI television show. The authors collected transcripts of 39 episodes and video/audio of 4 episodes. Each episode involves on average more than 30 speakers. Utterances last on average 3 to 4 seconds. There are around 45 to 50 distinct scenes/conversations per episode.
This is a dataset for coronavirus-themed malware for Android devices. It is a daily growing COVID-19 themed mobile app dataset, which contains 4,322 COVID-19 themed apk samples (2,500 unique apps) and 611 potential malware samples (370 unique malicious apps) by the time of mid-November, 2020.
This Dataset contains the IDs of 5,427,024 commit authors who have created commits in git version control system, and have more than 1 ID in git. It is a compressed CSV file (separated by ; ) with 14,861,538 author IDs, where the first column is the group ID, which is same as the first (randomly selected) author ID of the group, and the second column is the author ID that is part of the group. If an author was found to have 2 different IDs: I1, I2, then it is recorded in the file in 2 separate lines, with the lines being I1;I1 and I1;I2, i.e. the first column is the group identifier, which is one of the IDs in a group, and the second column contains the different author IDs in separate lines. This data set contains email addresses for various Git author's, but the '@' within the email address has been replaced with a '#'.
This dataset is a new variant of the voice cloning toolkit (VCTK) dataset: device-recorded VCTK (DR-VCTK), where the high-quality speech signals recorded in a semi-anechoic chamber using professional audio devices are played back and re-recorded in office environments using relatively inexpensive consumer devices.
Peer to Peer Hate is a comprehensive hate speech dataset capturing various types of hate. It has been built from 27,330 hate speech tweets.
Dense Forest Trail is an UAV dataset collected from a variety of simulated environment in Unreal Engine.
Dizi is a dataset of music style of the Northern school and the Southern School. Characteristics include melody and playing techniques of the two different music styles are deconstructed.
MARS Map is a set of three dataset collected to evaluate the performance of mapping algorithms within a room and between rooms.
The FFT-75 dataset contains randomly sampled, potentially overlapping file fragments from 75 popular file types. It is a diverse and balanced dataset which is labeled with class IDs and is ready for training supervised machine learning models. We distinguish 6 different scenarios with different granularity and provide variants with 512 and 4096-byte blocks. In each case, we sampled a balanced dataset and split the data as follows: 80% for training, 10% for testing and 10% for validation.
CapriDB is a 3D object database for robotics.
Xamarin Q&A consists of two datasets of questions and answers for studying the development of cross-platform mobile applications using the Xamarin framework. The two datasets were created by mining two Q&A sites: Xamarin Forum and Stack Overflow. The datasets have 85,908 questions mined from the Xamarin Forum and 44,434 from Stack Overflow.
The dataset is organized as follows. We have 8 different goals and 10 different world instances for both the domains, home and factory. Each domain has 8 directories corresponding to the goals possible for the domain. These goals itself, contain directories for the 10 different world instances. Each goal for each world instance in a particular domain thus has a number of different human demonstrations, and these are saved in the form of a .datapoint file for each plan.
This is a dataset that catalogs 2.6 million patents granted between 2005 and 2017.
This is a dataset of over 40K Reddit comments removed by moderators according to the specific type of macro norm being violated.