Classification algorithms in Data Mining
Data mining is a relevant term that simplifies the exploration and analysis of the huge amount of data with the aim of looking for hidden and valuable information from it. The area of interest among researchers in involving Data mining approaches to handle healthcare datasets have increased recently. In this context, we tried to categorize patients; who can be affected by breast cancer, diabetes or hypothyroidism; according to the stage of each disease. In fact, several classification algorithms; including SimpleLogistic, Instance-based k-nearest Neighbors (IBK), Naive Bayes, Stochastic Gradient Descent (SGD), Logistic model tree (LMT) and Sequential Minimal Optimization (SMO), are compared in terms of powerful performance measures. Therefore, after using the well-known data mining and knowledge discovery tool; Weka, we managed to pick the classification technique; LMT, which proved its high accuracy and scalability when dealing with healthcare datasets having different characteristics.
Disclaimer/Regarding indexing issue:
We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information. Also: DOI is paid service which provided by a third party. We never mentioned that we go for this for our any journal. However, journal have no objection if author go directly for this paid DOI service.