*.csv; *.zip
Decision-makers must make decisions under uncertainty. In the era of Data Analytics and ``data-driven" decision-making, decision-makers therefore need to understand the risk, variance and uncertainty in the data they are provided. While there has been a sizable research effort to investigate how to communicate risk to lay people better, the field of uncertainty visualization is much less-developed, with many questions still remaining how to best visualize variance and uncertainty.
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20 Views
The Unified Multimodal Network Intrusion Detection System (UM-NIDS) dataset is a comprehensive, standardized dataset that integrates network flow data, packet payload information, and contextual features, making it highly suitable for machine learning-based intrusion detection models. This dataset addresses key limitations in existing NIDS datasets, such as inconsistent feature sets and the lack of payload or time-window-based contextual features.
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2543 Views
SART contains 3000 tweets labelled with respect to the polarity of the sentiment expressed: positive, negative or neutral. Each class contains 1300 tweets and the dataset is split into train/validation/test csv files.
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29 Views
200 hours of accelerometer information recorded over 25 days from 5 participants.
To help us better understand the properties of various energy sources and their impact on energy harvesting adaptive algorithms, we collected acceleration traces from different participants.
release date: 2014-05-13
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167 Views
This dataset includes the rotor geometrical parameters (*.csv) and motor parameters (*.csv) of interior permanent magnet synchronous motors. The rotor geometry covers three structures: 2D-, V-, and Nabla-structures. The motor parameters are generated by machine learning based on the finite element analysis results. The software JMAG Designer 19.1 was used for the finite element analysis.
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601 Views
Although several databases of handwriting movements have been created so, none of them has been specifically designed for studying the effect of age during ellipse drawing. Ninety subjects voluntarily participated in the database construction. Their age ranged from 19 to 85 years: 30 participants in the range [19, 39] years, 30 in the range [40, 59] and 30 subjects in the range [60, 85]. Twenty-six women (range 19-72 years) and sixty-four men (range 25-85 years) participated.
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243 Views
One of the industries that uses Machine Learning is Radiation Oncology
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171 Views
We welcome any use of this openData package. For any questions or inquiries please get in touch with filip.milojkovic .at. beenera.de
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4079 Views