Results 21 to 30 of about 563,170 (163)
Generating Facial Composites from Principal Components
MATEC Web of Conferences, 2016 Penetrating computers and process automation into all the fields of human activity meant a breakthrough in the research of forensic methods applied on facial composite production.
Zahradnikova Barbora +2 more
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Principal components analysis of employment in Eastern Europe [PDF]
Panoeconomicus, 2006 For the last decade, the employment structure is one of the fastest changing areas of Eastern Europe. This paper explores the best methodology to compare the employment situations in the countries of this region.
Savić Mirko
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Principal volatil components of Txakoli of Bizkaia
OENO One, 1995 The aim of this work was to characterize the Txakoli of Bizkaia, a wine produced in the Basque Country. This note gives account of the volatile content of the wine which has been awarded by the Denominacíon de Origen Bizkaiko Txakolina quality label ...
Ana Escobal +2 more
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ANOVA bootstrapped principal components analysis for logistic regression
Croatian Review of Economic, Business and Social Statistics, 2022 Principal components analysis (PCA) is often used as a dimensionality reduction technique. A small number of principal components is selected to be used in a classification or a regression model to boost accuracy.
Toleva Borislava
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Recursive principal components analysis [PDF]
Neural Networks, 2005 A recurrent linear network can be trained with Oja's constrained Hebbian learning rule. As a result, the network learns to represent the temporal context associated to its input sequence. The operation performed by the network is a generalization of Principal Components Analysis (PCA) to time-series, called Recursive PCA. The representations learned by
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The Modified Principal Component Analysis Feature Extraction Method for the Task of Diagnosing Chronic Lymphocytic Leukemia Type B-CLL [PDF]
Journal of Universal Computer Science, 2020 The vast majority of medical problems are characterised by the relatively high spatial dimensionality of the task, which becomes problematic for many classic pattern recognition algorithms due to the well-known phenomenon of the curse of dimensionality ...
Mariusz Topolski
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PRINCIPAL COMPONENTS TO OVERCOME MULTICOLLINEARITY PROBLEM [PDF]
Oradea Journal of Business and Economics, 2019 The impact of ignoring collinearity among predictors is well documented in a statistical literature. An attempt has been made in this study to document application of Principal components as remedial solution to this problem.
Abubakari S.Gwelo
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Revista Ambiente & Água, 2021 “Erodibility” is a characteristic of the soil that represents the susceptibility with which its particles from the most superficial layer are taken and transported to lower places by erosive agents, causing environmental and economic damages.
Lucivânia Izidoro da Silva +6 more
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Principal Component Regression by Principal Component Selection
Communications for Statistical Applications and Methods, 2015 Abstract We propose a selection procedure of principal components in principal component regression. Our methodselects principal components using variable selection procedures instead of a small subset of major principalcomponents in principal component regression. Our procedure consists of two steps to improve estimation andprediction.
Hosung Lee, Yun Mi Park, Seokho Lee
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Principal Components Analysis Utility in the Livestock Field
Bulletin of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca. Animal Science and Biotechnologies, 2016 Principal Component Analysis is a method factor - factor analysis - and is used to reduce data complexity by replacingmassive data sets by smaller sets.
Ancuta Simona Rotaru +3 more
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