The k-nearest neighbour (KNN) technique is a simple yet effective method for classification. In this paper, we propose an efficient weighted nearest neighbour classification algorithm, called PINE, using vertical data representation. A metric called HOBBit is used as the distance metric. The PINE algorithm applies a Gaussian podium function to set weights to different neighbours. We compare PIN...

We derive an asymptotic expansion for the excess risk (regret) of a weighted nearest-neighbour classifier. This allows us to find the asymptotically optimal vector of nonnegative weights, which has a rather simple form. We show that the ratio of the regret of this classifier to that of an unweighted k-nearest neighbour classifier depends asymptotically only on the dimension d of the feature vec...

The main aim of this work is to measure and compare the accuracy prediction medical insurance using a Decision tree with K-nearest neighbor algorithm. Supervised Machine learning Techniques innovative Trees (N = 50) K Nearest Neighbour (KNN) are performed. In study, 100 photos were utilized, 80% them being trained 20% tested, sample size for two groups was computed G power pretest 0.8. Compared...

A bootstrap technique for nearest neighbor classifier design is proposed. Our primary interest in designing a classifier is in small training sample size situations. Conventional bootstrapping techniques sample the training samples with replacement. On the other hand, our technique generates bootstrap samples by locally combining original training samples. The nearest neighbor classifier is des...

In this paper, the nearest neighbor algorithm is used to evaluate soccer talents for suitable positions. In other words, the nearest neighbor algorithm is used as a suitable tool to investigate which position is suitable for a player considering his skills and characteristics. The combination of the information provided by some papers was used to specify the characteristics of each soccer playe...

Nearest neighbor (NN) classifier is the most popular non-parametric classifier. It is a simple classifier with no design phase and shows good performance. Important factors affecting the efficiency and performance of NN classifier are (i) memory required to store the training set, (ii) classification time required to search the nearest neighbor of a given test pattern, and (iii) due to the curs...

New Peer-to-Peer (P2P) applications like P2P jobemployee seeker networks and P2P virtual cities, for application domains such as collaborative urban planning and forming virtual communities, are about to emerge. An important component in these applications is spatial data, i.e., data with locational components. Many requests initiated on spatial data involve finding the spatial objects that are...

Categorization of texts into topical categories has gained booming interest over the past few years. There is a growing need for tools that help in finding, filtering and managing the highdimensional data due to the rapid growth of online information. Building a text classifier by hand is time consuming and costly and hence automated text categorization has gained a lot of importance. A general...

ABSTRACT- Cancer is one of the Non-Communicable Disease groups whose growth and development are high-speed. One type cancer breast (carcinoma mammae). Breast leading cause death for women. The first cells can grow into tumors as large 1 cm, spanning 8-12 years. prevalence rate in Indonesia 50 per 100,000 female population. method used this study uses K-Nearest Neighbor (K-NN) algorithm by compa...