Survey of Classification Techniques in Data Mining

The traditional KNN text classification algorithm has three limitations: (i) calculation complexity due to the usage of all the training samples for classification, (ii)

The objective of this research was to build up a model (decision tree) using data mining techniques such as feature selection and data classification, for predicting broiler

Esta pesquisa possui como objetivo avaliar a eficiência de novas fontes de coagulantes orgânicos originados a partir de restos alimentícios como cascas de frutas (casca

We compare a fuzzy-inference method with two other computational intelligence methods, decision trees and neural networks, using a case study of land cover classification from

For example, mean absolute error of J48 is minimum for breast cancer data set (i.e. small data set) but not minimum for sick data set (i.e. large data set) for from the table 1, it

In this study, Memory based classifiers are experimented to estimate classification accuracy of that classifier in a classification of Multivariate Data sets

Based on the results of our proposed method, fusion of classifiers on two data sets improves classification accuracy. Based on these results, proposed classifier

Recently, Gupta et al [9] examined the efficacy of three data mining techniques namely CART, Naïve Bayesian Classifier and Genetic Programming for detecting