In today world of internet, it is important to feedback the users based on what they demand. Moreover, one of the important tasks in data mining is classification. Today, there are several classification techniques in order to solve the classification problems like Genetic Algorithm, Decision Tree, Bayesian and others. In this article, it is attempted to classify researchers to “Expert” and “No...

Missing value imputation methods are widely used in solving missing value problems during statistical analysis. For classification tasks, these imputation methods can affect the accuracy of the Bayesian network classifiers. This paper study’s the effect of missing value treatment on the prediction accuracy of four Bayesian network classifiers used to predict death in acute chronic Hepatitis pat...

There are so many different varieties of vegetables in Indonesia that the sorting procedure presents difficulties. In an effort to expedite introduction smart farming Indonesia, more agricultural assistance techniques will be created. Utilizing Naive Bayes algorithm is one way may used advance agriculture Indonesia. Image processing consists converting RGB images grayscale images, segmenting us...

Kernel density estimation (KDE) is an important method in nonparametric learning. While KDE has been studied extensively in the context of accuracy of density estimation, it has not been studied extensively in the context of classification. This paper studies nine bandwidth selection schemes for kernel density estimation in Naive Bayesian classification context, using 52 machine learning benchm...

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© A Heterogeneous Naive-Bayesian Classifier for Relational Databases Geetha Manjunath, M Narasimha Murty, Dinkar Sitaram HP Laboratories HPL-2009-225 Relational databases, Classification, Data Mining, RDF Most enterprise data is distributed in multiple relational databases with expert-designed schema. Application of single-table data mining techniques to distributed relational data not only inc...