Results 61 to 70 of about 851,900 (211)
Uncertainty-Aware Principal Component Analysis
, 2019 We present a technique to perform dimensionality reduction on data that is subject to uncertainty. Our method is a generalization of traditional principal component analysis (PCA) to multivariate probability distributions.
Deussen, Oliver +4 more
core +1 more source
OPTIMALISASI HASIL PROSES WIRE-CUT EDM DENGAN METODE PRINCIPAL COMPONENT ANALYSIS (PCA)
Rotor: Jurnal Ilmiah Teknik Mesin, 2017 Some of the desired performance of the machining process Wire-Cut Electric Discharge Machining CV. Catur Prasetya Packindo is rate workmanship short and surface roughness of lower cutting. The problem is how to manage the performance of process variables
Mulyadi Mulyadi, Agus Puji Suryanto
doaj
Intelligent PharmacyIntroduction: Cephalosporins, a class of beta-lactam antibiotics, are commonly used in medical practice. However, their potential advantages, based on physicochemical and pharmacokinetic variables, are often overlooked.
Carlos Alberto Escobar Angulo +2 more
doaj +1 more source
Journal of Spectroscopy, 2021 To facilitate the enhanced reliability of Raman-based tumor detection and analytical methodologies, an ex vivo Raman spectral investigation was conducted to identify distinct compositional information of healthy (H), ductal carcinoma in situ (DCIS), and ...
Heping Li +7 more
doaj +1 more source
Image encoding by independent principal components [PDF]
, 2010 The encoding of images by semantic entities is still an unresolved task. This paper proposes the encoding of images by only a few important components or image primitives. Classically, this can be done by the Principal Component Analysis (PCA). Recently,
Arlt, Björn, Brause, Rüdiger W.
core
Nucleic Acids Res., 2015 The Principal Component Analysis (PCA) is a widely used method of reducing the dimensionality of high-dimensional data, often followed by visualizing two of the components on the scatterplot. Although widely used, the method is lacking an easy-to-use web
Tauno Metsalu, J. Vilo
semanticscholar +1 more source
An Infinitesimal Probabilistic Model for Principal Component Analysis of Manifold Valued Data
, 2018 We provide a probabilistic and infinitesimal view of how the principal component analysis procedure (PCA) can be generalized to analysis of nonlinear manifold valued data. Starting with the probabilistic PCA interpretation of the Euclidean PCA procedure,
Sommer, Stefan
core +1 more source
A least squares approach to Principal Component Analysis for interval valued data [PDF]
Principal Component Analysis (PCA) is a well known technique the aim of which is to synthesize huge amounts of numerical data by means of a low number of unobserved variables, called components.
D'Urso, Pierpaolo, Giordani, Paolo
core
Implementasi Principal Component Analysis (PCA) Untuk Pengenalan Wajah Manusia [PDF]
, 2015 - Pada zaman modern ini, perkembangan teknologi terutama di dunia digital, membawa Perubahan cukup besar. Salah satunya sistem pencitraan digital.Sistem pencitraan digital mempunyai sifat yang efisien,lebih akurat dan sistematis.
Firliana, R. (Rina) +2 more
core
ACCPlot: gráficos del ACP con Mathematica
Revista de Matemática: Teoría y Aplicaciones, 2009 ACPPlot is a command for creating graphics for Principal Component Analysis (PCA), principal planes and correlation circles; in both cases, adding options for joining points with trajectories, clustering points, labeling and for improving the general ...
Carlos Arce Salas
doaj +1 more source