Machine Learning
Contains 12 datasets for feature selection dimensionality reduction and machine learning.
The dimension of the selected datasets ranges from 10 to 1000, and the number of instances ranges from 200 to 3000.
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FARLEAD2 receives a test scenario from the developer, and verifies a related functional behavior by witnessing the test scenario in the Application Under Test, on a real mobile device. The 'results.zip' file contains 204 Comma-Separated Values (CSV) files and a Perl script 'createtable.pl' that generates Table 2 in the manuscript. Each CSV file contains the results of ten runs of a witness generator for a test scenario under a given level of information. The experimental test scenarios are located in the 'scenarios.zip' file.
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The support dataset for paper "Prediction for loosening life of bolted joints using IMUs with dimensionality reduction"
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Anthropometric studies focusing on facial metrics and their proportions form an important research area devoted to observations of the appearance of the human skull. Many different applications include the use of craniometry for maxillofacial reconstruction and surgery. The paper and the associated dataset explores the possibility of using selected craniometric points and associated metric to observe spatial changes during the maxillofacial surgery treatment. The experimental dataset includes observations of 27 individuals.
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130 videos are available, captured in Patras, Greece, displaying drivers in real cars, moving under nighttime conditions where drowsiness detection is more important.The participating drivers are: 11 males and 10 females with different features (hair color, beard, glasses, etc). The videos are split in 2 categories:
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content-based dataset that composes of 12 features for eight common types of files (JPG, PNG, HTML, TXT, MP4, M4A, MOV, and MP3) to be suitable for file type identification (FTI). These features were extracted from pool of file fragment of size 512 byte each from all the prementioned eight types. This dataset is developed in such a way that can be used for supervised and unsupervised ML model. It provides the ability to classifying and clustering the above-mentioned type into two levels.
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The data of the AC report are collected from the website JUCHAO(http://www.cninfo.com) through the crawler process of Python.
The text feature data is obtained by computing AC reports with the machine learning and text analysis methods of Python.
The data includes 1349 firms from 2014-2019, with 6987 observations.
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Early detection of retinal diseases is one of the most important means of preventing partial or permanent blindness in patients. One of the major stumbling blocks for manual retinal examination is the lack of a sufficient number of qualified medical personnel per capita to diagnose diseases.
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