Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
February 17, 2026
Neural Networks and Rules-based Systems used to Find Rational and
Article Fingerprint
ReserarchID
CSTSDE33X91
Dr. K.Venkat Nagarjuna
The Bayesian classifier is a fundamental classification technique. We also consider different concepts regarding Dimensionality Reduction techniques for retrieving lossless data. In this paper, we proposed a new architecture for pre-processing the data. Here we improved our Bayesian classifier to produce more accurate models with skewed distributions, data sets with missing information, and subsets of points having significant overlap with each other, which are known issues for clustering algorithms. so, we are interested in combining Dimensionality Reduction technique like PCA with Bayesian Classifiers to accelerate computations and evaluate complex mathematical equations. The proposed architecture in this project contains the following stages: pre-processing of input data, Naïve Bayesian classifier, Bayesian classifier, Principal component analysis, and database. Principal Component Analysis(PCA) is the process of reducing components by calculating Eigen values and Eigen Vectors. We consider two algorithms in this paper: Bayesian Classifier based on KMeans( BKM) and Naïve Bayesian Classifier Algorithm(NB).
Dr. K.Venkat Nagarjuna. 2012. \u201cBayesian Classifiers Programmed In SQL Using PCA\u201d. Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 12 (GJCST Volume 12 Issue C13): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
The methods for personal identification and authentication are no exception.
The methods for personal identification and authentication are no exception.
Neural Networks and Rules-based Systems used to Find Rational and
A Comparative Study of the Effeect of Promotion on Employee
The Problem Managing Bicycling Mobility in Latin American Cities: Ciclovias
Impact of Capillarity-Induced Rising Damp on the Energy Performance of
The Bayesian classifier is a fundamental classification technique. We also consider different concepts regarding Dimensionality Reduction techniques for retrieving lossless data. In this paper, we proposed a new architecture for pre-processing the data. Here we improved our Bayesian classifier to produce more accurate models with skewed distributions, data sets with missing information, and subsets of points having significant overlap with each other, which are known issues for clustering algorithms. so, we are interested in combining Dimensionality Reduction technique like PCA with Bayesian Classifiers to accelerate computations and evaluate complex mathematical equations. The proposed architecture in this project contains the following stages: pre-processing of input data, Naïve Bayesian classifier, Bayesian classifier, Principal component analysis, and database. Principal Component Analysis(PCA) is the process of reducing components by calculating Eigen values and Eigen Vectors. We consider two algorithms in this paper: Bayesian Classifier based on KMeans( BKM) and Naïve Bayesian Classifier Algorithm(NB).
We are currently updating this article page for a better experience.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.
