Heart failure is included in the category of cardiovascular disease. disease not easy to detect, and its detection needs be done by experienced skilled medical professionals. Most patients with heart require hospitalization. Common symptoms disease, such as chest pain high or low blood pressure, vary from person person. This study aims find most optimal k value based on accuracy obtained calcul...

Fuzzy Inductive Reasoning (FIR) is a methodology for qualitative modeling and simulation of systems behavior. FIR inference engine is based on the k-nearest neighbor (k-NN) rule, commonly used in the Pattern Recognition eld. The adaptation of the k-NN in an ad hoc 5-NN method has been proved to be very successful in the past, obtaining good results for diierent kind of systems. However, in some...

This paper presents the results of the application of an instance based learning algorithm k Nearest Neighbor Method on Fea ture Projections k NNFP to text categorization and compares it with k Nearest Neighbor Classi er k NN k NNFP is similar to k NN ex cept it nds the nearest neighbors according to each feature separately Then it combines these predictions using a majority voting This prop er...

Seperti kota lain yang berada di pulau Jawa, Banyuwangi memiliki batik khas sendiri. Motif juga keunikan sendiri, apalagi motif dimiliki sangat beragam. Sejarah dan filosofi dari batiknya menarik terutama gajah oling merupakan tertua paling dikenal wilayah Banyuwangi. Dimana generasi orang muda saat ini sudah tidak bisa mengenali daerah asalnya, mengklasifikasikan menurut filosofi, jenis, warna...

Detection and estimation of causality relationships between two random processes is a fundamental problem in many natural and social sciences [1]. This task is in particular challenging as in many real-life scenarios one does not have a good underlying statistical model for the considered process, e.g., in the fields of neuroscience, financial markets, meteorology, etc. For such scenarios it is...

In this paper, a theoretical framework is proposed for the introduction of the K-NN pdf estimator in an HMM-based speech recognition system. The estimation of the state output probabilities with the K-NN pdf estimator is shown to imply the introduction of a new parameter : the membership coefficient. To learn this coefficient with the Baum-Welch algorithm, a maximum likelihood (ML) reestimation...

Confidence measures for k-NN classification are an important aspect of building practical systems for online handwritten character recognition. In many cases, the distribution of training samples across the different classes is marked by significant skew, either as a consequence of unbalanced data collection or because the application itself incrementally adds samples to the training set over a...