Results 31 to 40 of about 9,360,077 (298)

Locality Preserving Projection Method Based on Optimal Nearest Neighbor [PDF]

open access: yesJisuanji gongcheng
Locality Preserving Projection(LPP) is a classical dimensionality reduction method used in machine learning. However, the LPP method and some improved methods simply use the k-Nearest Neighbor(k-NN) classification algorithm to find the nearest neighbors ...
ZHAO Juntao, LI Taoshen, LU Zhixiang
doaj   +1 more source

k-nearest neighbors in uncertain graphs [PDF]

open access: yesProceedings of the VLDB Endowment, 2010
Complex networks, such as biological, social, and communication networks, often entail uncertainty, and thus, can be modeled as probabilistic graphs . Similar to the problem of similarity search in standard graphs, a fundamental problem for probabilistic graphs is to efficiently answer k-nearest neighbor
Michalis Potamias   +3 more
openaire   +1 more source

K-Nearest Neighbor and Naive Bayes Classifier Algorithm in Determining The Classification of Healthy Card Indonesia Giving to The Poor

open access: yesScientific Journal of Informatics, 2018
Health is a human right and one of the elements of welfare that must be realized in the form of giving various health efforts to all the people of Indonesia.
Yofi Firdan Safri   +2 more
doaj   +1 more source

Implementasi Algoritma K-Nearest Neighbor Berbasis Forward Selection Untuk Prediksi Mahasiswa Non Aktif Universitas Dian Nuswantoro Semarang

open access: yesJOINS (Journal of Information System), 2020
Masalah yang muncul berkaitan dengan status mahasiswa salah satunya adalah status mahasiswa yang non aktif. Beberapa faktor penyebab status non aktif tersebut diantaranya adalah faktor ekonomi, kemampuan akademik, dan lain – lain.
Abu Salam   +2 more
doaj   +1 more source

Multi-type K-nearest Neighbor Query Scheme with Mutual Privacy-preserving in Road Networks [PDF]

open access: yesJisuanji kexue
In the Internet of vehicles scenario,existing location-based service privacy-preserving schemes have issues such as not supporting parallel query of multi-type K-nearest neighbor points of interest,difficulty to protect the privacy of both the in-vehicle
ZENG Congai, LIU Yali, CHEN Shuyi, ZHU Xiuping, NING Jianting
doaj   +1 more source

k-Nearest Neighbor with Map Reduce MPI

open access: yes, 2023
Contribution for Peachy Assignment presented at EduHPC 2023; see https://tcpp.cs.gsu.edu/curriculum/?q=peachy for the assignment repository.Assignment to implement k-nearest neighbor in map reduce paradigm on top of MPI.
Erik Saule (17378589)
core   +1 more source

Face Identification Based on K-Nearest Neighbor

open access: yesScientific Journal of Informatics, 2019
Face identification has been widely applied this time, such as security on gadgets, smart home security, and others. Face dominates as a biometric which is most increase in the next few years. Face is used for biometric identification which is considered
Ni Kadek Ayu Wirdiani   +5 more
doaj   +1 more source

Klasifikasi Kopra Putih Menggunakan Algoritma k-Nearest Neighbor

open access: yesSistemasi: Jurnal Sistem Informasi, 2021
Buah kelapa adalah bagian pohon kelapa yang sering dimanfaatkan untuk kehidupan manusia yaitu kehidupan pangan, daunnya sering dimanfaatkan untuk pembuatan kerajinan tangan di beberapa daerah, batangnya sering digunakan untuk bahan bangunan, selain itu ...
Rosi Rahayu Marlis   +2 more
doaj   +1 more source

Analisis Performa Algoritma K-Nearest Neighbor dan Reduksi Dimensi Menggunakan Principal Component Analysis

open access: yesJambura Journal of Mathematics, 2023
This paper discusses the performance of the K-Nearest Neighbor Algorithm with dimension reduction using Principal Component Analysis (PCA) in the case of diabetes disease classification.
Aldila Dinanti, Joko Purwadi
doaj   +1 more source

Navigating K-Nearest Neighbor Graphs to Solve Nearest Neighbor Searches [PDF]

open access: yes, 2010
Nearest neighbor queries can be satisfied, in principle, with a greedy algorithm under a proximity graph. Each object in the database is represented by a node, and proximal nodes in this graph will share an edge. To find the nearest neighbor the idea is quite simple, we start in a random node and get iteratively closer to the nearest neighbor following
Edgar Chávez, Eric Sadit Tellez
openaire   +2 more sources

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