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APPLICATION OF PRINCIPAL COMPONENT ANALYSIS TO DROUGHT INDICATORS OF THREE REPRESENTATIVE CROATIAN REGIONS [PDF]
Drought has become a very frequent hydrological event globally, including in Croatia. It can generally be explained by air temperature and precipitation changes on an annual and seasonal basis, owing to climate change.
Lidija Tadić +3 more
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Classification and analysis of the MNIST dataset using PCA and SVM algorithms
Introduction/purpose: The utilization of machine learning methods has become indispensable in analyzing large-scale, complex data in contemporary data-driven environments, with a diverse range of applications from optimizing business operations to ...
Mokhaled N. A. Al-Hamadani
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The ‘Žutica’ represents the most common Montenegrin olive varieties mainly used for the production of olive oil and green and black fruit canning.
Mirjana ADAKALIĆ +5 more
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Principal Component Analysis Based Wavelet Transform [PDF]
The principal component analysis (PCA) is a valuable statistical means, implemented in time domain that has found application in many fields such as face recognition and image compression, and is a common technique for finding patterns in data of high ...
Hana M. Salman
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RKF-PCA: Robust kernel fuzzy PCA
Principal component analysis (PCA) is a mathematical method that reduces the dimensionality of the data while retaining most of the variation in the data. Although PCA has been applied in many areas successfully, it suffers from sensitivity to noise and is limited to linear principal components.
Computer and Information Science and Engineering, University of Florida, United States ( host institution ) +3 more
openaire +4 more sources
Stream sediment samples play an important role in identifying potential areas of metallic and non-metallic mineralization in mineral exploration studies.
Aref Shirazi +4 more
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Phylogenetic PCA (p-PCA) is a version of PCA for observations that are leaf nodes of a phylogenetic tree. P-PCA accounts for the fact that such observations are not independent, due to shared evolutionary history. The method works on Euclidean data, but in evolutionary biology there is a need for applying it to data on manifolds, particularly shapes ...
Morten Akhøj +2 more
openaire +4 more sources
Aphelenchoides bicaudatus associated with grass in South Africa was identified morphologically and molecularly. This population is characterized by a body length of 409 – 529 μm, a stylet length of 9.5 – 13 μm, a post-vulval uterine sac of 45 – 50 μm ...
Shokoohi E., Moyo N. A. G.
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Dimensionality Reduction: Challenges and Solutions [PDF]
The use of dimensionality reduction techniques is a keystone for analyzing and interpreting high dimensional data. These techniques gather several data features of interest, such as dynamical structure, input-output relationships, the correlation between
Ahmad Noor, Nassif Ali Bou
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Potential Partnerships: Progressive Criminology, Grassroots Organizations and Social Justice
Criminologists around the globe are writing about the disproportionate criminalization of minority groups and – in the US in particular – about racial disproportionality in all aspects of the criminal justice system.
Tim Goddard +2 more
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