Principal component analysis

Page 1 of 50 - About 500 essays
  • Principal Components Analysis ( Pca ) Versus Principal Axes Factors

    2012 Words  | 9 Pages

    Principal Components Analysis (PCA) versus Principal Axes Factors (PAF) and Other Extraction Methods Broadly, conducting factor analysis (FA) allows a researcher to analyze or interpret his or her data (e.g., measured variables) by reducing those variables into factors or components that underlie the structure or explain the greatest amount of variance in the data (Thompson, 2004). Thompson (2004) also tells us that FA may be used for many purposes, the most common of which is to uncover a relationship

  • Water Quality Data ( Fixed Interval Sampling )

    1762 Words  | 8 Pages

    Buffalo Creek basins over a 15-year period was obtained from The City of Greensboro Stormwater Division, North Carolina. The sampled data were grouped in ranges of years from 1999-2002, 2003-2008, 2009-2010 and 2011-2013 so as to obtain a detailed analysis on the data. The sampling sites in the study area were numbered for simplicity of result presentation. Sites 1 to 6 were located at the highly sub-urban and agricultural area and sites 7 to 18 were located in the highly urbanized area of Greensboro

  • Spss on Spending Habits of Students

    2110 Words  | 9 Pages

    TOPIC:- “RELEVANCE OF POLITICS IN EDUCATIONAL INSTITUTIONS” INTRODUCTION The main objective of doing multivariate data analysis is to determine the practical significance of the various issues. That means whether the study is useful in future or not. That is why I am taking the topic “RELEVANCE OF POLITICS”. Politics is an ever relevant topic in a country like India because India is a democratic nation. Nothing will happen with out a political influence. At present the politicians decides

  • Image Fusion Technique Based on PCA and Fuzzy Logic Essay

    707 Words  | 3 Pages

    This paper presents a image fusion technique based on PCA and fuzzy logic. the framework of the proposed image fusion technique is divided in the following major phases:  preprocesing phase  Feature extraction based on the principal component analysis  The image fusion based on fuzzy set  Reconstruction final image The figure (1) shows the framework of the proposed image fusion and its phases. Fig. 1. The proposed approach of image fusion phases A. Preprocessing Phase This phase consists of three

  • Brief Explanation of the Basic Framework of the Principal Componant Analysis and Fuzzy Logic

    573 Words  | 3 Pages

    basic frame-work of the principal component analysis and fuzzy logic, along with some of the key basic concepts. A. The principal component analysis (PCA) The Principal component analysis (PCA) is an essential technique in data compression and feature reduction [13] and it is a statistical technique applied to reduce a set of correlated variables to smaller uncorrelated variables to each other. PCA is considered as special transformation which produces the principal components (PCs) Known as eigenvectors

  • Knowledge Transfer Advantages And Disadvantages

    4367 Words  | 18 Pages

    CHAPTER - 5 DISCUSSIONS AND CONCLUSIONS Introduction This chapter summarizes the analytical findings and draws conclusions. The findings and the relevance of them for implementation and limitations and scope for further research are described. This study on knowledge transfer, a process in the overall schema of knowledge management, as fostering continual improvement of the organization was done at High Pressure Boiler Plant of Bharat Heavy Electricals Limited Tiruchirappalli. Knowledge transfer

  • The Human Visual System ( Hvs ) For More Secure And Effective Data Hiding

    1337 Words  | 6 Pages

    Research in the field of watermarking is flourishing providing techniques to protect copyright of intellectual property. Among the various methods that exploits the characteristics of the Human Visual System (HVS) for more secure and effective data hiding, wavelet based watermarking techniques shows to be immune to attacks, adding the quality of robustness to protect the hidden message of third party modifications. In this paper, we introduced non blind with DWT & SVD . Also we applies a casting

  • Document Analysis Using Latent Semantic Indexing With Robust Principal

    11097 Words  | 45 Pages

    Document Analysis Using Latent Semantic Indexing with Robust Principal Component Analysis Turki Fisal Aljrees School of Science and Technology Middlesex University Registration report MPhil / PhD June 2015 Acknowledgements I would like to acknowledge Director of Study Dr. Daming Shi, My Second Supervisor: Dr. David Windridge , and Dr. George Dafoulas Abstract There are numerous data mining techniques have been developed and used recently in text documents. Using and update discovered a pattern

  • Factor Analysis: An Analysis Of Brand Choice Factors

    742 Words  | 3 Pages

    customers to choose from. Brand recognition is the area to which a brand is accepted for stated brand choice factors. The technique used to analyze brand choice factors is factor analysis. It focused on brand choice factors of respondents. Major variables that determine the brand selection are presented for further factor analysis and ANOVA is used in order to analyses the factors For that, first correlation matrix is formed to find the appropriateness of factor model by checking whether such correlated

  • Measuring Team Work On Health Care Settings

    1499 Words  | 6 Pages

    concept being studied (Aday & Cornelius, 2006). In order to assist this first step, definitions of the three constructs; collaboration, communication and trust will be given to the experts. A Content Validity Index will be used to assist in this analysis (Table 1). Evaluating a scale’s content validity is a critical early step in enhancing the overall validity of an instrument (Beck & Polit, 2006; Beck, Owen & Polit, 2007). As mentioned above, content validity concerns the degree to which a scale