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Principal Component Analysis (PCA)

Building Machine Learning and Deep Learning Models on Google Cloud Platform, 2019
Principal component analysis (PCA) is an essential algorithm in machine learning. It is a mathematical method for evaluating the principal components of a dataset. The principal components are a set of vectors in high-dimensional space that capture the variance (i.e., spread) or variability of the feature space.
S. Raschka
openaire   +2 more sources

The use of principal component analysis (PCA) to characterize beef

Meat Science, 2000
Principal component analysis was performed to study the relationships between chemical, physical and sensory variables (n=18) measured on longissimus thoracis et lumborum of 79 young bulls from the following ethnic groups: hypertrophied Piemontese, normal Piemontese, Friesian, crossbred hypertrophied Piemontese×Friesian, Belgian Blue and White.
DESTEFANIS, Gianluigi   +3 more
openaire   +4 more sources

Investigation of correlation between chemical composition and properties of biodiesel using principal component analysis (PCA) and artificial neural network (ANN)

, 2021
Biodiesel will provide a significant renewable energy source for transportation in the near future. In the present study, principal component analysis (PCA) has been used to understand the relationship between important properties of biodiesel and its ...
M. Jahirul   +7 more
semanticscholar   +1 more source

Information-theoretic feature selection with segmentation-based folded principal component analysis (PCA) for hyperspectral image classification

International Journal of Remote Sensing, 2020
Hyperspectral image (HSI) usually holds information of land cover classes as a set of many contiguous narrow spectral wavelength bands. For its efficient thematic mapping or classification, band (feature) reduction strategies through Feature Extraction ...
Md. Palash Uddin   +3 more
semanticscholar   +1 more source

Principal components analysis (PCA)

Computers & Geosciences, 1993
Principal Components Analysis (PCA) as a method of multivariate statistics was created before the Second World War. However, the wider application of this method only occurred in the 1960s, during the “Quantitative Revolution” in the Natural and Social Sciences.
Andrzej Maćkiewicz, Waldemar Ratajczak
openaire   +1 more source

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