Principle component analysis (PCA) (factor analysis)
Sentimental Analysis of Tweets using Principle Component Analysis Technique
... Principle Component Analysis (PCA) is a dimensionality reduction technique that is commonly used to transform a high- dimensional sample to small dimension by finding a new set of variables, smaller ...
6
Face Recognition using Eigenvector and Principle Component Analysis
... 2.2 Principle Component Analysis (PCA) Technique PCA is one of the most successful techniques that have been used in face ...Principal Component Analysis is to take the total variation ...
8
A Comparative Study on using Principle Component Analysis with different Text Classifiers
... New Valley, Egypt ABSTRACT Text categorization (TC) is the task of automatically organizing a set of documents into a set of pre-defined categories. Over the last few years, increased attention has been paid to the use ...
6
Multiobjective differential evolution enhanced with principle component analysis for constrained optimization
... of Principle Component Analysis in Evolutionary algorithms It is an interesting idea to apply PCA to the design of EAs but so far only a few research papers can be found on this ...
28
Hyperspectral Images Classification via Weighted Spatial Spectral Principle Component Analysis
... Conclusion This paper proposed a new weighted spatial and spectral principle component analysis (WSSPCA) algorithm. This algorithm considers the physical characteristics to reconstruct the HSI by ...
7
Efficient Image Recognition Technique Using Invariant Moments and Principle Component Analysis
... 6. Conclusion In this research, we are looking to make efficient recognition way for large data- sets by using Invariant Moments and Principle Component Analysis (PCA). Be- sides that, we are looking ...
11
Celiac Disease Seen with the Eyes of the Principle Component Analysis and Analyse Des Données
... the principle component analysis (pca) and the Analyse des Données to further study the risk [7] [8] and therefore dietary transgression (Figure ...
12
Anomaly network intrusion detection method in network security based on principle component analysis
... on Principle Component Analysis (PCA) for data reduction and classifier in ...preliminary analysis using a set of benchmark data from KDD (Knowledge Discovery and Data Mining) Competition ...
11
Principle Component Analysis and Partial Least Squares: Two Dimension Reduction Techniques for Regression
... multivariate analysis, it is especially critical for multivariate regressions in many P&C insurance-related ...methodologies, principle component analysis (PCA) and partial least squares ...
12
Motion Classification Using Proposed Principle Component Analysis Hybrid K Means Clustering
... others. Principle Component Analysis (PCA) was used to reduce the number of variables, from six to three; to re- duce the complexity of large data ...
6
A New Digital Video Watermarking Using Decimated Wavelet and Principle Component Analysis in YCbCr Domain
... 3.2. Principle Component Analysis It is a mathematical procedure that uses the orthogonal transformation to convert a set of observations of possible correlated variables into a set of values of ...
8
A Comparative Study of Locality Preserving Projection and Principle Component Analysis on Classification Performance Using Logistic Regression
... algorithms principle component analysis (PCA) and locality pre- serving projections (LPP) to reduce the dimensions using dimensionality reduction toolbox (drtoolbox) in mat- lab ...ROC ...
9
Classification of Machine Fault using Principle Component Analysis, General Regression Neural Network and Probabilistic Neural Network
... Abstract—As a major industry prime mover, induction motor plays an important role in manufacturing. In fact, production can cease its operation if there is some error or fault in the induction motor. In the industry, ...
6
Fault diagnosis of rolling element bearing based on wavelet kernel principle component analysis-coupled hidden Markov model
... kernel principle component analysis Various feature parameters are expected to be obtained so as to reflect the running state of the machinery ...extent. Principle components analysis ...
15
Weighted Principle Component Analysis For Dimensionality Reduction In Medical Dataset
... Clustering, Principle Component Analysis, WPCA, Feature Selection, ...data analysis tools to discover pattern and relationship in data that may be used to make valid ...
6
A Effective Disease Prediction Model Using Enhanced Principle Component Analysis And Mdrp Algorithm
... The study proposed a Data mining model has been developed using Enhanced Principle Component Analysis to improve the Disease prediction accuracy and to investigate the risk level of the disease. The ...
8
Assessment for Urban Eco-Communities : A Case Study of Principle Component Analysis Method in Taipei, Taiwan
... applied principle component analysis method to study the eco- community of ...by principle component analysis, and divides 456 administrative area of Taipei into 5 kind’s impact ...
7
The Prediction Model of Financial Crisis Based on the Combination of Principle Component Analysis and Support Vector Machine
... Abstract This paper studies financial crisis of listed companies in China Manufacture Industry, and selects 181 companies with financial crisis and 181 normal companies as its research samples, and its research is based ...
9
An Effective early stage Disease Prediction Model Using Enhanced Principle Component Analysis and MDRP Algorithm
... FDP Substitute lecturer, Department of Computer Science, KAHM Unity Women's College, Manjeri, Malappuram, Kerala, India 1 Corresponding Author: Basheer. P Abstract: Data mining on medical data has great potential to ...
8
Improving the quality of images synthesized by discrete cosine transform regression-based method using principle component analysis
... Using principle component analysis instead of DCT In signal and image processing, DCT is often applied because of its lossy data compression and strong energy ...here principle ...
6