K-nearest neighbor (KNN)
Reasonable Estimated K Nearest Neighbor Queries with Locality and Query Privacy
... approximate k nearest neighbor (KNN) queries where the mobile user queries the location-based service (LBS) provider about approximate k nearest points of interest (POIs) based on his ...
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DETECTION OF HIGH IMPEDANCE FAULTS IN DISTRIBUTION FEEDERS - K-NEAREST NEIGHBOR METHOD
... trained k-Nearest Neighbor Method (KNN) are used as a classifier processing, to classify the state of each ...and k- Nearest Neighbor Method (KNN) this different stages of the ...
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Improve Adaptive k-Nearest Neighbor Algorithm using Multi-threading
... traditional k-nearest neighbor (kNN) algorithm is one of the oldest method for ...of nearest neighbors for each test ...adaptive k-nearest neighbor (AdaNN) ...optimal ...
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Automated Car Number Plate Recognition System using K Nearest Neighbor
... classification. K-Nearest Neighbor classifier is a simple classifying approach in the machine learning methods where the classification is attained through the identification of the adjacent ...
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Alphabet Sign Language Recognition Using K-Nearest Neighbor Optimization
... is K-Nearest Neighbor (K-NN) [1]. K-NN is a famous method for image classification, which is because it’s simple and easy to be ...standalone K-NN doesn’t have a good in accuracy ...
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K-Nearest Neighbor Classification over Semantically Secure Encrypted Relational Data
... the k-nearest neighbor (kNN) query problem over encrypted database outsourced to a cloud: a user issues an encrypted query record to the cloud, and the cloud returns the k closest records to ...
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A Novel Weighted Voting for K-Nearest Neighbor Rule
... sub-optimal k is greatly affected by the finite sample space in the practical ...if k is too small, the classification result of the query is sensitive to the data sparseness and the noisy, ambiguous or ...
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Identification Of Speaker Recognition For Audio Forensic Using K-Nearest Neighbor
... -Nearest Neighbor (KNN) is a method used to classify objects based on learning data that has the closest distance to the object, this method aims to classify recently entered objects based on training data ...
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Authentication of k Nearest Neighbor Query on Road networks using Voronoi diagram
... network k-nearest-neighbor question verification technique that utilizes the network Voronoi diagram and neighbors to prove the integrity of query ...verifies k -nearest-neighbor ...
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Pruned fuzzy K nearest neighbor classifier for beat classification
... Arrhythmia beat classification is an active area of research in ECG based clinical decision support sys- tems. In this paper, Pruned Fuzzy K-nearest neighbor (PFKNN) classifier is proposed to ...
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K-Nearest Neighbor Classification Mechanism of Secure Encrypted Relational Data
... the k-nearest neighbor (kNN) query problem over encrypted database outsourced to a cloud: a user issues an encrypted query record to the cloud, and the cloud returns the k closest records to ...
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Evaluating the Performance of Dual Weighted K Nearest Neighbor Classifier
... A non-parametric, very simple to use, effective instance-based learning algorithm called K-Nearest Neighbor (KNN), is most widely used to classify the objects in data mining. KNN has some ...
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Semantic Word Categorization using Feature Similarity based K Nearest Neighbor
... This article proposes the modified KNN (K Nearest Neighbor) algorithm which considers the feature similarity and is applied to the word categorization. The texts which are given as features for ...
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What Affects K Value Selection In K-Nearest Neighbor
... K-NEAREST NEIGHBOR classifier is a popular classifier that has been applied in many fields, such as in text categorization [2], intrusion detection [3], handwritten digit recognition [4], alternative ...
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Embedding k-Nearest Neighbor Queries into Relational Database Management Systems
... the k- Nearest Neighbor (k-NN) comparison operator gives ground to conflicting interpretations when composed with ...on k-NN are embedded into a RDBMS, formalize the possible ...
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Classification Of Medical Image Data Using K Nearest Neighbor And Finding The Optimal K Value
... into k NN classifiers. Findings presented that the k NN degraded performance due to its inability of handling high dimensional ...using k NN is a tedious task due to higher mean squared ...using ...
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A Short Term Traffic Flow Forecasting Method Based on a Three Layer K Nearest Neighbor Non Parametric Regression Algorithm
... However, road traffic system is a nonlinear system characterized by time-dependence and complexity and ex- hibits a distinctive feature—high uncertainty, which makes the forecasting model based on a single-layer ...
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A Dependent Multilabel Classification Method Derived from the k-Nearest Neighbor Rule
... In this paper, we present a generalization of the MLkNN- based approach to multilabel classification problems where the dependencies between classes are considered. We call this method DMLkNN, for dependent multilabel ...
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Evaluation Of The Performance Of K-Nearest Neighbor Algorithm In Determining Student Learning Styles
... techniques: K-Nearest Neighbor algorithm and Support Vector Machine with the purpose of finding a model that has the high performance of the new cases of the test ...the K-NN technique ...
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Rate of Convergence of $k$-Nearest-Neighbor Classification Rule
... the k-nearest- neighbor classification rule according to the error probability of the Bayes decision is revis- ited by a decomposition of the excess error probability into approximation and ...
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