principal component analysis and classification (PCCA)
Automated web pages classification with integration of principal component analysis (PCA) and independent component analysis (ICA) as feature reduction
... pages classification has become an essential ...pages classification will provide an efficient information search to internet ...professional classification, a website would become a jumble yard of ...
6
Principal Component Analysis for Dimensionality Reduction for Animal Classification based on LR
... Abstract: Nowadays, data generation is huge in nature and there is a need for analysis, visualization and prediction. Data scientists find many difficulties in processing the data at once due to its massive ...
6
Classification for Damage Severity in Natural Fibre Composites Using Principal Component Analysis
... modified Principal Component Analysis (PCA) method and simple pattern recognition ...damage classification method for delaminated smart composite laminates using ...based classification ...
6
Relevance Vector Machine Classification of Hyperspectral Data Based on Principal Component Analysis and Linear Discriminant Analysis
... the classification accuracy of RVM is not high when apply to hyperspectral ...novel classification method based on RVM is presented in this ...combine principal component analysis (PCA) ...
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Principal Component Analysis for Supervised Learning: a minimum classification error approach
... Principal Component Analysis (PCA) is a technique used to reduce data dimensionality. It projects data points into the directions of maximal variance within data space. These directions are the ...
15
Simulation of pornography web sites (PWS) classification using principal component analysis with neural network
... content analysis based filtering is being introduced to overcome this ...content analysis, features extraction techniques play an important role to extract appropriate features from large volume of web ...
13
Kernel Principal Component Analysis for the Classification of Hyperspectral Remote Sensing Data over Urban Areas
... Kernel principal component analysis (KPCA) is investigated for feature extraction from hyperspectral remote sensing ...kernel principal component features are more linearly separable ...
14
Fingerprint Based Gender Classification Using 2D Discrete Wavelet Transforms and Principal Component Analysis
... The algorithm that was developed was simple which was to study how well frequency domain analysis help in the classification. In future the algorithm has to be improved with a good classification ...
5
MRI BRAIN IMAGE CLASSIFICATION USING POLYNOMIAL KERNEL PRINCIPAL COMPONENT ANALYSIS WITH NEURAL NETWORK
... Various classification rates are obtained using different power of applied ...by classification gives, ...higher classification accuracy for large MRI ...
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Classification of Malaysian honey using fourier transform infrared spectrroscopy and principal component analysis
... indicates classification of pure honey from different location where the pure honey from Pahang is located at the positive value while the pure honey from Melaka is at the negative side of PC 2 ...
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Cancer Classification using Principal Component Analysis and Deep Neural Networks
... Principal Component Analysis (PCA) is a linear dimensionality reduction method that generates linear combinations of original features that are capable of projecting original data on a reduced ...
10
Automated Classification of Brain Tumors using Image Pre Processing and Probabilistic Neural Networks
... tumor classification using an amalgamation of image processing techniques and artificial ...values. Principal component analysis is used for reduction of the dimensionality of the training ...
5
Mixed PCA and Wavelet Transform based Effective Feature Extraction for Efficient Tumor Classification using DNA Microarray Gene Expression Data
... Discriminant Analysis (LDA) also fall under a peculiar category of feature transformation where in the former uses a statistical signal criterion whereas the latter uses a classification ...Local ...
7
The Effects of Extreme Media on Political Behavior, Attitudes, and Media Selection
... the classification of different things is a natural process for human ...cluster analysis from data mining point of view that “Cluster analysis divides data into groups that are meaningful, useful, ...
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Comparison of Neural Networks and Support Vector Machines using PCA and ICA for Feature Reduction
... page classification provides an efficient information search to internet ...statistical analysis methods known as Principal Component Analysis (PCA) and Independent Component ...
6
A Novel Intrusion Detection System Based On Kpca And Rvm With Pso Model
... A classification technique, relevance vector machine (RVM) model combining kernel principal component analysis (KPCA) with particle swarm optimization (PSO) is proposed for intrusion detection ...
8
Total luminescence spectroscopy for differentiating between brandies and wine distillates
... variate analysis methods, Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA), were applied separately on the excitation and emission ...any classification ...
8
A Model for African Fabrics Analysis and Recognition
... level classification scheme. In the first scheme, principal component analysis and Discrete Wavelet Transform (DWT) were combined for multi-level decomposition and classification among ...
6
Dimensionality Reduction Techniques for Improved Diagnosis of Heart Disease
... Medical diagnosis is an important task that needs to be executed accurately and efficiently. Medical domain complexities are represented by multidimensional heterogeneous datasets. Computer aided diagnosis must deal with ...
8
Monitoring the occurrence of frost through an analysis of air masses in south west basins of Iran
... movement, persistency, extension of air masses, advection frosts in the area under study could be identified. Then the patterns that cause the occurrence of advection frosts can become known and the results applied to ...
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