The performance of a new hybrid classifier based on boxes and nearest neighbors
نویسندگان
چکیده
In this paper we present a new type of binary classifier defined on the unit cube. This classifier combines some of the aspects of the standard methods that have been used in the logical analysis of data (LAD) and geometric classifiers, with a nearest-neighbor paradigm. We assess the predictive performance of the new classifier in learning from a sample, obtaining generalization error bounds that improve as the ‘sample width’ of the classifier increases.
منابع مشابه
A New Hybrid Approach of K-Nearest Neighbors Algorithm with Particle Swarm Optimization for E-Mail Spam Detection
Emails are one of the fastest economic communications. Increasing email users has caused the increase of spam in recent years. As we know, spam not only damages user’s profits, time-consuming and bandwidth, but also has become as a risk to efficiency, reliability, and security of a network. Spam developers are always trying to find ways to escape the existing filters therefore new filters to de...
متن کاملA Novel Hybrid Approach for Email Spam Detection based on Scatter Search Algorithm and K-Nearest Neighbors
Because cyberspace and Internet predominate in the life of users, in addition to business opportunities and time reductions, threats like information theft, penetration into systems, etc. are included in the field of hardware and software. Security is the top priority to prevent a cyber-attack that users should initially be detecting the type of attacks because virtual environments are not moni...
متن کاملA comparative study of performance of K-nearest neighbors and support vector machines for classification of groundwater
The aim of this work is to examine the feasibilities of the support vector machines (SVMs) and K-nearest neighbor (K-NN) classifier methods for the classification of an aquifer in the Khuzestan Province, Iran. For this purpose, 17 groundwater quality variables including EC, TDS, turbidity, pH, total hardness, Ca, Mg, total alkalinity, sulfate, nitrate, nitrite, fluoride, phosphate, Fe, Mn, Cu, ...
متن کاملThe Performance of small samples in quantifying structure central Zagros forests utilizing the indexes based on the nearest neighbors
Abstract Todaychr('39')s forest structure issue has converted to one of the main ecological debates in forest science. Determination of forest structure characteristics is necessary to investigate stands changing process, for silviculture interventions and revival operations planning. In order to investigate structure of the part of Ghale-Gol forests in Khorramabad, a set of indices such as Cla...
متن کاملA New Hybrid Framework for Filter based Feature Selection using Information Gain and Symmetric Uncertainty (TECHNICAL NOTE)
Feature selection is a pre-processing technique used for eliminating the irrelevant and redundant features which results in enhancing the performance of the classifiers. When a dataset contains more irrelevant and redundant features, it fails to increase the accuracy and also reduces the performance of the classifiers. To avoid them, this paper presents a new hybrid feature selection method usi...
متن کامل