Dengue is a threatening disease caused by female mosquitos. It is typically found in widespread hot regions. From long periods of time, Experts are trying to find out some of features on Dengue disease so that they can rightly categorize patients because different patients require different types of treatment. Pakistan has been target of Dengue disease from last few years. Dengue fever is used ...

The increase of students’ drop out rate in higher education is one of the important problems in most institutions. The discovery of hidden knowledge from the educational data system by the effective process of data mining technology to analyze factors affecting student drop out can lead to a better academic planning and management to reduce students drop out rate, as well as can inform valuable...

Particle Swarm Optimisers are inherently distributed algorithms where the solution for a problem emerges from the interactions between many simple individual agents called particles. This article proposes the use of the Particle Swarm Optimiser as a new tool for Data Mining. In the first phase of our research, three different Particle Swarm Data Mining Algorithms were implemented and tested aga...

s Accepted or Presented since last Annual Report Prediction of MortalitySlaughter G, Kurtz Z, desJardins M, Hu PF, Mackenzie C, Stansbury L, Stein DM.2012 IEEE Biomedical Circuits & Systems conference, Nov 28-30, Taiwan Abstract— Real-time patient monitoring data collected over the course of trauma care are often large inquantities and require systematic representation that can comb...

This research work deals with efficient data mining procedure for predicting the diabetes from medical records of patients. Diabetes is a very common disease these days in all populations and in all age groups. Diabetes contributes to heart disease, increases the risks of developing kidney disease, nerve damage, blood vessel damage and blindness. So mining the diabetes data in efficient manner ...

When machine learning (ML) and data mining (DM) methods construct models in complex domains, models can contain less-credible parts [2], which are statistically significant, but meaningless to the human analyst. For example, let us consider a decision tree model presented in Figure 1. The tree is constructed with the J48 algorithm in Weka [8] for a complex domain indicating which segments of re...

results overall, the prevalence of unwanted pregnancies was 32.3%. the performance of the models based on the area under the roc curve as the indicator was as follows: artificial neural networks (0.741), decision tree (0.731), and logistic regression (0.712). the highest sensitivity level belonged to the decision tree (73.5%), and the highest specificity level belonged to the artificial neural ...

Learning from imbalanced data is an important problem in data mining research. Much research has addressed the problem of imbalanced data by using sampling methods to generate an equally balanced training set to improve the performance of the prediction models, but it is unclear what ratio of class distribution is best for training a prediction model. Bagging is one of the most popular and effe...