Results 21 to 30 of about 104,528 (306)

Weighted k-Nearest-Neighbor Techniques and Ordinal Classification [PDF]

, 2004
In the field of statistical discrimination k-nearest neighbor classification is a well-known, easy and successful method. In this paper we present an extended version of this technique, where the distances of the nearest neighbors can be taken into ...
Schliep, Klaus, Schliep, K., Hechenbichler, Klaus, Hechenbichler, K.   +3 more
core   +1 more source

Feature Selection and Weighting by Nearest Neighbor Ensembles [PDF]

, 2008
In the field of statistical discrimination nearest neighbor methods are a well known, quite simple but successful nonparametric classification tool. In higher dimensions, however, predictive power normally deteriorates. In general, if some covariates are
Gertheiss, Jan, Gerhard Tutz, Jan Gertheiss, Tutz, Gerhard   +3 more
core   +1 more source

Continuous Nearest Neighbor Queries over Sliding Windows [PDF]

, 2007
—This paper studies continuous monitoring of nearest neighbor (NN) queries over sliding window streams. According to this model, data points continuously stream in the system, and they are considered valid only while they belong to a sliding window that ...
Papadias, Dimitris, Dimitris Papadias, Kyriakos Mouratidis, MOURATIDIS, Kyriakos   +3 more
core   +1 more source

The K-Nearest Neighbor algorithm using Forward Selection and Backward Elimination in predicting the Student’s Satisfaction Level of University Ichsan Gorontalo toward Online Lectures during the COVID-19 Pandemic

Ilkom Jurnal Ilmiah, 2023
Academic services are actions taken by state and private universities to provide convenience for student’s academic activities. During the current covid-19 pandemic, every university remains active in academic activities.
Andi Bode, Zulfrianto Y Lamasigi, Ivo Colanus Rally Drajana   +2 more
doaj   +1 more source

Local feature weighting in nearest prototype classification [PDF]

, 2008
The distance metric is the corner stone of nearest neighbor (NN)-based methods, and therefore, of nearest prototype (NP) algorithms. That is because they classify depending on the similarity of the data.
Isasi, Pedro, Fernández, Fernando, Isasi Viñuela, Pedro   +2 more
core   +1 more source

Random k conditional nearest neighbor for high-dimensional data [PDF]

PeerJ Computer Science
The k nearest neighbor (kNN) approach is a simple and effective algorithm for classification and a number of variants have been proposed based on the kNN algorithm. One of the limitations of kNN is that the method may be less effective when data contains
Jiaxuan Lu, Hyukjun Gweon
doaj   +2 more sources

ALGORITMA K-NEAREST NEIGHBOR TERHADAP PELUANG MAHASISWA MENJADI AKTIVIS KAMPUS PADA JURUSAN MATEMATIKA UNIVERSITAS NEGERI PADANG

Jurnal Lebesgue, 2023
The purpose of this study was to predict whether mathematics students at Padang State University have the opportunity to become campus activists using the K-Nearest Neighbor Algorithm (KNN). This research will be used as a benchmark to calculate how many
Muhammad Fadhli Gusvino, Defri Ahmad
doaj   +1 more source

Lip language identification via Wavelet entropy and K-nearest neighbor algorithm

EAI Endorsed Transactions on e-Learning, 2021
INTRODUCTION: Image processing technology is widely used in lip recognition, which can automatically detect and analyse the unstable shape of human lips.
Ran Wang, Yifan Cui, Xinyu Gao, Wei Chen, Mingbo Hu, Qian Li, Jiahui Wei, XianWei Jiang   +7 more
doaj   +1 more source

Two-Pass K Nearest Neighbor Search for Feature Tracking

IEEE Access, 2018
In recent years, feature tracking has become one of the most important research topics in computer vision. Many efforts have been made to design excellent feature matching methods. For large-scale structure from motion, however, existing feature tracking
Mingwei Cao, Wei Jia, Zhihan Lv, Wenjun Xie, Liping Zheng, Xiaoping Liu   +5 more
doaj   +1 more source

Network intrusion detection based on random k-nearest neighbor ensemble algorithm

Nantong Daxue xuebao. Ziran kexue ban, 2023
To improve the accuracy and generalization of network intrusion detection models, a model based on the random k-nearest neighbor(k-NN) ensemble algorithm is proposed for network flow intrusion detection.
ZHANG Chengye; LI Zhuoxuan; CAO Jinde
doaj   +1 more source