Results 271 to 280 of about 88,237 (314)

The MST-kNN with Paracliques

2015
In this work, we incorporate new edges from a paraclique-identification approach to the output of the MST-kNN graph partitioning method. We present a statistical analysis of the results on a dataset originated from a computational linguistic study of 84 Indo-European languages.
Ahmed Shamsul Arefin, Carlos Riveros, Regina Berretta, Pablo Moscato   +3 more
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Analysis and evaluation of V*-kNN: an efficient algorithm for moving kNN queries

The VLDB Journal, 2009
The moving k nearest neighbor (MkNN) query continuously finds the k nearest neighbors of a moving query point. MkNN queries can be efficiently processed through the use of safe regions. In general, a safe region is a region within which the query point can move without changing the query answer.
Sarana Nutanong, Rui Zhang 0003, Egemen Tanin, Lars Kulik   +3 more
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Heart Disease Prediction Using Extended KNN (E-KNN)

2021
The WHO estimates that deaths due to heart disease are the number one cause worldwide, accounting for around 30% annually taking an estimated 1.5 crores who die due to this disease. In this study, an extension of KNN algorithm known as E-KNN is used and compares with the results of different machine learning methods such as K-Nearest Neighbor (KNN ...
R. Sateesh Kumar, S. Sameen Fatima
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G-KNN

Proceedings of the 30th Annual ACM Symposium on Applied Computing, 2015
In nowadays we observe that there is more data than that can be effectively analyzed. Organizing this data has become one of the biggest problems in Computer Science. Many algorithms have been proposed for this purpose, highlighting those related to the Data Mining area, specifically the automatic document classification (ADC) algorithms.
Leonardo Rocha 0001, Gabriel Spada Ramos, Rodrigo Chaves, Rafael Sachetto Oliveira, Daniel Madeira, Felipe Viegas, Guilherme Andrade, Sérgio Daniel, Marcos André Gonçalves, Renato Ferreira 0001   +9 more
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The kNN Model

2021
In this chapter, you will discover the kNN model. The kNN model is the third supervised machine learning model that is covered in this book. Like the two previous models, the kNN model is also one of the simpler models. It is also intuitively easy to understand how the model works.
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Classification of Gunshots with KNN Classifier

Proceedings of the Euro American Conference on Telematics and Information Systems, 2018
In this article a system of detection and classification of gunshots is proposed, which consists of using the KNN classifier in the presence and absence of Gaussian additive noise. The results guarantee that the classifier reaches up to 94 % of performance in the absence of noise and only using 10 attributes. The attributes proposed in this article are
Francisco D. Pichardo-Morales, Marco A. Acevedo-Mosqueda, Sandra L. Gomez Coronel   +2 more
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A granular, parametric KNN classifier

Proceedings of the 17th Panhellenic Conference on Informatics, 2013
This work presents a granular K Nearest Neighbor, or grKNN for short, classifier in the metric lattice of Intervals' Numbers (INs). An IN here represents a population of numeric data samples. We detail how the grKNN classifier can be parameterized towards optimizing it.
Vassilis Tsoukalas, Vassilis G. Kaburlasos, Christos Skourlas   +2 more
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Distributed kNN Query Authentication

2018 19th IEEE International Conference on Mobile Data Management (MDM), 2018
With the prevalence of location-based services and geo-functioned devices, the trend of spatial data outsourcing is rising. In the data outsourcing scenario, result integrity must be ensured by means of a query authentication scheme. However, most of the existing studies are confined to a centralized environment. In this paper, we investigate the query
Ce Zhang, Cheng Xu, Jianliang Xu, Byron Choi   +3 more
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Random KNN

2014 IEEE International Conference on Data Mining Workshop, 2014
Shengqiao Li, E. James Harner, Donald A. Adjeroh   +2 more
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Classification by Weighting, Similarity and kNN

2006
In this paper, the grouping method of the similar words, is proposed for the classification of documents. It is shown that the grouping of words has equivalent ability to the LSA in the classification accuracy. Further, a new combining method is proposed for the documents classification, which consists of Grouping, Latent Semantic Analysis(LSA ...
Naohiro Ishii, Tsuyoshi Murai, Takahiro Yamada, Yongguang Bao   +3 more
openaire   +1 more source