Generating Firm's Performance Indicators by Applying PCA
نویسندگان
چکیده
منابع مشابه
Applying Indicators to Improve Health System Performance
The cycle of performance measurement and management begins with explicitly establishing goals which are reflected in the adoption of specific performance indicators, followed by analysis and actions aimed at producing change to improve performance in a variety of dimensions such as equity, access, effectiveness, efficiency and social responsiveness. The application of performance indicators may...
متن کاملEnvironmental performance indicators: an empirical study of Canadian manufacturing firms.
The aim of this exploratory study is to examine the importance of measurement and use of environmental performance indicators (EPIs) within manufacturing firms. Two research questions are investigated: (i) To what extent are firm characteristics associated with the importance of measurement of various categories of EPIs? (ii) To what extent are firm characteristics associated with global and sp...
متن کاملGait Recognition by Applying Multiple Projections and Kernel PCA
Recognizing people by gait has a unique advantage over other biometrics: it has potential for use at a distance when other biometrics might be at too low a resolution, or might be obscured. In this paper, an improved method for gait recognition is proposed. The proposed work introduces a nonlinear machine learning method, kernel Principal Component Analysis (KPCA), to extract gait features from...
متن کاملPalmprint Recognition by Applying Wavelet Subband Representation and Kernel PCA
This paper presents a novel Daubechies-based kernel Principal Component Analysis (PCA) method by integrating the Daubechies wavelet representation of palm images and the kernel PCA method for palmprint recognition. The palmprint is first transformed into the wavelet domain to decompose palm images and the lowest resolution subband coefficients are chosen for palm representation. The kernel PCA ...
متن کاملApplying Discrete PCA in Data Analysis
Methods for analysis of principal components in discrete data have existed for some time under various names such as grade of membership modelling, probabilistic latent semantic analysis, and genotype inference with admixture. In this paper we explore a number of extensions to the common theory, and present some application of these methods to some common statistical tasks. We show that these m...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Korean Institute of Intelligent Systems
سال: 2015
ISSN: 1976-9172
DOI: 10.5391/jkiis.2015.25.2.191