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Asdrúbal López-Chau, Lisbeth Rodriguez-Mazahua, Farid García-Lamont, Maricela Quintana-López and Carlos A. Rojas-Hernández
A test of independence is commonly used to determine differences (or associations) between samples in a nominal level measurement. Fisher?s exact test and Chi-square test are two of the most widely applied tests of independence used in the data analyses ...
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Camil Bancioiu and Remus Brad
This article proposes the usage of the d-separation criterion in Markov Boundary Discovery algorithms, instead of or alongside the statistical tests of conditional independence these algorithms usually rely on. This is a methodological improvement applic...
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Tatjana Bolic, Lorenzo Castelli, Andrea De Lorenzo and Fulvio Vascotto
Availability of different types of data and advances in data-driven techniques open the path to more detailed analyses of various phenomena. Here, we examine the insights that can be gained through the analysis of historical flight trajectories, using da...
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Laith R. Sultan, Theodore W. Cary, Maryam Al-Hasani, Mrigendra B. Karmacharya, Santosh S. Venkatesh, Charles-Antoine Assenmacher, Enrico Radaelli and Chandra M. Sehgal
Machine learning for medical imaging not only requires sufficient amounts of data for training and testing but also that the data be independent. It is common to see highly interdependent data whenever there are inherent correlations between observations...
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Ram M. Narayanan, Michael J. Harner, John R. Jendzurski and Nicholas G. Paulter
Through-wall and through-barrier motion-sensing systems are becoming increasingly important tools to locate humans concealed behind barriers and under rubble. The sensing performance of these systems is best determined with appropriately designed calibra...
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