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Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing. The data is linearly transformed onto a new coordinate system such that the directions (principal components) capturing the largest variation in the data can be easily identified.
The Presbyterian Church in America (PCA) is the second-largest Presbyterian church body, behind the Presbyterian Church (USA), and the largest conservative Calvinist denomination in the United States. The PCA is Reformed in theology and presbyterian in government.
The PCA begins as a continuation of the posterior communicating artery in 70-90% of fetuses with the remainder of PCAs having a basilar origin. The fetal carotid origin of the PCA usually regresses as the vertebral and basilar arteries become dominant and it finds a new origin in the basilar artery.
The following are central branches of the PCA, also known as perforating branches: Thalamoperforating and thalamogeniculate or postero-medial ganglionic branches: a group of small arteries which arise at the commencement of the posterior cerebral artery: these, with similar branches from the posterior communicating, pierce the posterior perforated substance, and supply the medial surfaces of ...
L1-norm principal component analysis (L1-PCA) is a general method for multivariate data analysis. [1] L1-PCA is often preferred over standard L2-norm principal component analysis (PCA) when the analyzed data may contain outliers (faulty values or corruptions), as it is believed to be robust .
Patient-controlled analgesia (PCA [1]) is any method of allowing a person in pain to administer their own pain relief. [2] The infusion is programmable by the prescriber. If it is programmed and functioning as intended, the machine is unlikely to deliver an overdose of medication. [ 3 ]
In the field of multivariate statistics, kernel principal component analysis (kernel PCA) [1] is an extension of principal component analysis (PCA) using techniques of kernel methods. Using a kernel, the originally linear operations of PCA are performed in a reproducing kernel Hilbert space .
PCA may refer to: Medicine and biology. Patient-controlled analgesia; Plate count agar in microbiology; Polymerase cycling assembly, for large DNA oligonucleotides;