Results 11 to 20 of about 304,299 (338)
Use the robust RFCH method with a polychoric correlation matrix in structural equation modeling When you are ordinal data [PDF]
المجلة العراقية للعلوم الاحصائية, 2022 Structural Equation Modeling is a statistical methodology commonly used in the social and administrative sciences and all other. In this research, the researcher made a comparison between methods of estimation Unweighted Least Squares with Mean and ...
Omar Salim, Mohammed Mohammed
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Boscovich Fuzzy Regression Line
Mathematics, 2021 We introduce a new fuzzy linear regression method. The method is capable of approximating fuzzy relationships between an independent and a dependent variable.
Pavel Škrabánek +2 more
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LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks [PDF]
AAAI Conference on Artificial Intelligence, 2021 Many well-established anomaly detection methods use the distance of a sample to those in its local neighbourhood: so-called `local outlier methods', such as LOF and DBSCAN.
Adam Goodge +3 more
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International Journal of STEM Education, 2020 Background As the number of computer science (CS) jobs become increasingly available in this country and computing skills become essential tools for managing all aspects of our personal lives, CS is quickly becoming an essential element of K-12 education
Jeanne Century +2 more
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Study on the Technology Trend Screening Framework Using Unsupervised Learning
Applied Sciences, 2022 Outliers that deviate from a normal distribution are typically removed during the analysis process. However, the patterns of outliers are recognized as important information in the outlier detection method.
Junseok Lee, Sangsung Park, Juhyun Lee
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Remote Sensing, 2022 Heavy metal concentrations of Cd, As, Pb, Cu, Cr, and Hg were investigated for 86 soil samples in Jinzhou near the Bohai Sea in China, in order to identify what anthropological activities influenced their distribution levels. Ordinary cokriging (OCK) was
Ling Zeng +3 more
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On Selection Criteria for the Tuning Parameter in Robust Divergence
Entropy, 2021 Although robust divergence, such as density power divergence and γ-divergence, is helpful for robust statistical inference in the presence of outliers, the tuning parameter that controls the degree of robustness is chosen in a rule-of-thumb, which may ...
Shonosuke Sugasawa, Shouto Yonekura
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Frontiers in Physiology, 2023 As an important technique for data pre-processing, outlier detection plays a crucial role in various real applications and has gained substantial attention, especially in medical fields.
Jia Li +5 more
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Applied Sciences, 2020 This paper presents a novel framework for fraud detection in healthcare systems which self-learns from the historical medical data. Historical medical records are required for training and testing of machine learning models.
Irum Matloob +3 more
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Comparison of Different Response Time Outlier Exclusion Methods: A Simulation Study
Frontiers in Psychology, 2021 In response time (RT) research, RT outliers are typically excluded from statistical analysis to improve the signal-to-noise ratio. Nevertheless, there exist several methods for outlier exclusion.
Alexander Berger, M. Kiefer
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