A Comparative Study of Principal Component Analysis Techniques
نویسندگان
چکیده
Principal Component Analysis (PCA) is a useful technique for reducing the dimensionality of datasets for compression or recognition purposes. Many different methods have been proposed for performing PCA. This study aims to compare these methods by analysing the solutions which these methods find. We have estimated the correlation between these solutions and produced the errors using bootstrap resampling.
منابع مشابه
Combined Unfolded Principal Component Analysis and Artificial Neural Network for Determination of Ibuprofen in Human Serum by Three-Dimensional Excitation–Emission Matrix Fluorescence Spectroscopy
This study describes a simple and rapid approach of monitoring ibuprofen (IBP). Unfolded principal component analysis-artificial neural network (UPCA-ANN) and excitation-emission spectra resulted from spectrofluorimetry method were combined to develop new model in the determination of IBF in human serum samples. Fluorescence landscapes with excitation wavelengths from 235 to 265 nm and emission...
متن کاملCombined Unfolded Principal Component Analysis and Artificial Neural Network for Determination of Ibuprofen in Human Serum by Three-Dimensional Excitation–Emission Matrix Fluorescence Spectroscopy
This study describes a simple and rapid approach of monitoring ibuprofen (IBP). Unfolded principal component analysis-artificial neural network (UPCA-ANN) and excitation-emission spectra resulted from spectrofluorimetry method were combined to develop new model in the determination of IBF in human serum samples. Fluorescence landscapes with excitation wavelengths from 235 to 265 nm and emission...
متن کاملDiscrimination of Golab apple storage time using acoustic impulse response and LDA and QDA discriminant analysis techniques
ABSTRACT- Firmness is one of the most important quality indicators for apple fruits, which is highly correlated with the storage time. The acoustic impulse response technique is one of the most commonly used nondestructive detection methods for evaluating apple firmness. This paper presents a non-destructive method for classification of Iranian apple (Malus domestica Borkh. cv. Golab) according...
متن کاملExploring Gördes Zeolite Sites by Feature Oriented Principle Component Analysis of LANDSAT Images
Recent studies showed that remote sensing (RS) is an effective, efficient and reliable technique used in almost all the areas of earth sciences. Remote sensing as being a technique started with aerial photographs and then developed employing the multi-spectral satellite images. Nowadays, it benefits from hyper-spectral, RADAR and LIDAR data as well. This potential has widen its applicability in...
متن کاملSparse Structured Principal Component Analysis and Model Learning for Classification and Quality Detection of Rice Grains
In scientific and commercial fields associated with modern agriculture, the categorization of different rice types and determination of its quality is very important. Various image processing algorithms are applied in recent years to detect different agricultural products. The problem of rice classification and quality detection in this paper is presented based on model learning concepts includ...
متن کاملInvestors' Perception of Bank Risk Management: Multivariate Analysis Techniques
According to the nature of their activities, banks are exposed to various types of risks. Hence, risk management is at the heart of financial institutions management. In this study, we intend to summarize the information content of bank financial statements on diverse risks faced by banks and then determine how stock markets react to bank's risk management behavior. The methodology used in this...
متن کامل