To maximize and get population document services closer to the community, Disdukcapil district of Alor provides mobile by visiting people in remote villages which difficult-to-reach service centres city. Due a large number limited time costs, not all can be served, so kNN algorithm is needed determine are eligible served. The criteria used this determination village distance, difficulty level, ...

Heart failure is a type of disease that has the largest number patients in world. Based on information from data center, there were 229,696 people with heart 2013. Lack public knowledge about what indications person having make main cause not handled properly by patients. In this study, classification was carried out using KNN algorithm because it simple calculation and fast time. This study on...

Dalam beberapa instansi pengelolaan beasiswa masih menggunakan microsoft excel dan pemilihan penerima seleksi administrasis ecara manual. Salah satu pengolahan data dalam jumlah yang besar adalah mining. Oleh karena itu penelitian ini bertujuan untuk menerapkan mining dengan metode k-nearest neighbor (K-NN) penentuan beasiswa. Metode pengumpulan private, studi literatur, wawancara. Tahapan yait...

We investigate the task of compressing an image by using different probability models for compressing different regions of the image. In this task, using a larger number of regions would result in better compression, but would also require more bits for describing the regions and the probability models used in the regions. We discuss using quadtree methods for performing the compression. We int...

The approximate k-NN search algorithms are well-known for their high concert in high dimensional data. The locality-sensitive hashing (LSH) method, that uses a number of hash functions, is one of the most fascinating hash-based approaches. The k-nearest neighbour approaches based Various-Widths Clustering (kNNVWC) has been widely used as a prevailing non-parametric technique in many scientific ...

Analogy-based reasoning methods in machine learning make it possible to reason about properties of objects on the basis of similarities between objects. A specific similarity based method is the k nearest neighbors (k-nn) classification algorithm. In the k-nn algorithm, a decision about a new object x is inferred on the basis of a fixed number k of the objects most similar to x in a given set o...

The k-Nearest Neighbour (k-NN) method is a typical lazy learning paradigm for solving classification problems. Although this method was originally proposed as a non-parameterised method, attribute weight setting has been commonly adopted to deal with irrelevant attributes. In this paper, we propose a new attribute weight setting method for k-NN based classifiers using quadratic programming, whi...

Amphiphilic pseudo-amino acid composition (Am-Pse-AAC) with extra sequence-order information is a useful feature for representing enzymes. This study first utilizes the k-nearest neighbor (k-NN) rule to analyze the distribution of enzymes in the Am-Pse-AAC feature space. This analysis indicates the distributions of multiple classes of enzymes are highly overlapped. To cope with the overlap prob...

Abstract: Subset selection regression is a frequently used statistical method. It waives some of the predictor variables and the prediction equation is based on the remaining set of variables. Subset selection is simple and it clearly reduces the variance. An other method for reducing the variance is ridge regression. Usually, subset selection is not as accurate as ridge. The problems with ridg...