The present case study describes the results of the educational data mining aimed at predicting the undergraduate courses of computer science (BCA and B.Tech.) students’ instant dropout or after first semester. For this purpose, the preliminary data of 220 students collected randomly in prescheduled format on personal interview to find out dropout rates and dropout reasons. The simple and intui...

introduction the increasing use of satellite remote sensing data for civilian use has proved to be the most cost-effective means of mapping and monitoring for environmental changes. satellite remote sensing has played a pivotal role in finding forest cover, vegetation type and land use changes in urban areas. one of the most complete of these methods is classification. the conventional per-pixe...

Various statistical classification methods, including discriminant analysis, logistic regression, and cluster analysis, have been used with antibiotic resistance analysis (ARA) data to construct models for bacterial source tracking (BST). We applied the statistical method known as classification trees to build a model for BST for the Anacostia Watershed in Maryland. Classification trees have mo...

conclusions by comparing the results of classification using multiple classifier fusion with respect to using each classifier separately, it is found that the classifier fusion is more effective in enhancing the detection accuracy. objectives through the improvement of classification accuracy rate, this work aims to present a computer-assisted diagnosis system for malaria parasite. materials an...

<span>Methamphetamine addiction is a prominent problem in Southeast Asia. Drug addicts often discuss illegal activities on popular social networking services. These individuals spread messages media as means of both buying and selling drugs online. This paper proposes model, the “text classification model methamphetamine tweets Asia” (TMTA), to identify whether tweet from Asia related abu...

The advancement in computers provided large amount of data. The task is to analyse the input data and obtain the required data which can be done by various data mining techniques. The diagnosis of diabetes is a significant and tedious task in medicine. So the present work focus on analysis of diabetes data by various data mining techniques which involve,Naive Bayes, J48(C4.5) JRip ,Neural netwo...

Data mining term is mainly used for the specific set of six activities namely Classification, Estimation, Prediction, Affinity grouping or Association rules, Clustering, Description and Visualization. The first three tasks classification, estimation and prediction are all examples of directed data mining or supervised learning. Decision Tree (DT) is one of the most popular choices for learning ...