and KNN
Improved Outlier Detection using Classic KNN Algorithm
... events or observations which do not conform to an expected pattern or other items in dataset. The identification of instances that diverge from the expected behavior is a important task. Existing techniques provides a ...
7
Private kNN Query Processing in Cloud Enviroments
... In the planned research work, we emphasis on solving the k-nearest national (kNN) query problem over encoded database outsourced to a mist: a user issues an encoded query record to the cloud, then the cloud ...
5
MIME KNN: Improve KNN Classifier Performance Include Classification Accuracy and Time Consumption
... new KNN optimization algorithm MIME-KNN is ...the KNN algorithm and reduce the time complexity and space ...classical KNN algorithm. The experiment result shows that MIME-KNN can ...
11
Comparison: KNN & SVM Algorithm
... Abstract: The importance of image classification in the field of Machine Learning cannot be understated. Specifically, the use of algorithms such as KNN and SVM are the core engines behind the proper functioning ...
6
Friend Recommendation in KNN Classification
... ABSTRACT:OSN is an online service that facilitating the building of social relations among people.OSNs attracted by thousands of million people.OSN users extending their social circles by friend recommendations.During ...
5
Document Classification Using KNN on GPU
... A parallelized implementation of an proposed algorithm can run 70% of the algorithm's operations arbitrarily quickly (while the remaining 30% of the operations are not parallelizable), Amdahl's law states that the ...
6
Digits and Character Recognition using KNN
... Abstract: The proposed work is about offline recognition of digits and characters using machine learning. MNIST dataset has CSV file. From this, image is obtained by reading it. Then it is preprocessed using RGB ...
5
Algebraic Properties to Optimize kNN Queries
... approaches were combined to extend the relational algebra over domains enabled to be evaluated by similarity. Also, the concept of a ranked table based on the calculus of fuzzy relations was introduced. Pursuing the ...
16
Using KNN Method for Educational and Vocational Guidance
... the KNN method is used to determine the closest trades to an individual according to his profile calculated by using three criteria: professional interests of Holland (the RIASEC model), business sectors and the ...
7
An Efficient Image Retrieval System By Optimizing KNN
... using KNN to retrieve images from ...the KNN based similarity measure, images that are relevant to the QI were retrieved ...proposed KNN algorithm has strong capability to discriminate color, shape ...
7
Location Aware Query Reorganisation using KNN
... Abstract— Location-based services (LBS) enable mobile users to query points-of-interest (e.g., restaurants, cafes) on various features (e.g., price, quality). In addition, users require accurate query results with ...
5
An Efficient KNN Classification by using Combination of Additive and Multiplicative Data Perturbation for Privacy Preserving Data Mining
... for KNN classification as a tool for privacy-preserving data ...that KNN Classification algorithm can be efficiently applied to the transformed data and produce exactly the same results as if applied to the ...
6
Application of KNN-Genetic Algorithm for Analysing Student Learning in Educational Data Mining Paradigm
... Initially, various data mining techniques have been introducedfor the classification of the students’ data in educational data mining paradigm. K-nearest neighbor (K-nearest neighbor) has been proven to be the most ...
5
A Movement Decomposition And Knn-Based Fall Detection
... fall detection solutions using accelerometer-.. based method are evaluated2[r] ...
17
2004-CACIC-Knn
... O sistema constr´oi um conjunto de treinamento (a partir de uma colec¸˜ao de documentos com seus respectivos sum´arios) onde cada exemplo corresponde a uma sentenc¸a do documento origina[r] ...
10
An Implementation of Web Recommendation System using Web Usage Mining Technique
... the KNN (k-nearest neighbor) algorithm and correlation coefficient is used where the KNN is used to finding the data similar to user query and for finding the relevant content and to rank the content and ...
7
Design of a hybrid model for cardiac arrhythmia classification based on Daubechies wavelet transform
... Objectives. The aim of this work was to design a hybrid classification model to classify cardiac arrhythmias. Material and methods. The design phase of the classification model comprises the following stages: ...
8
Local K-Nearest Neighbors Model using Z-Order R-Tree for Big Data
... To obtain a speed improvement, many practical applications are forced to settle for an approximate search, where not all the neighbors returned are exact, but typically still close to the exact neighbors [6]. Packing the ...
6
Acceleration of k-Nearest Neighbor and SRAD Algorithms Using Intel FPGA SDK for OpenCL
... work, kNN using bitonic sorting algorithm, kNN using radix sorting algorithm and SRAD are implemented using IFSO targeting Intel Stratix V A7 and Arria 10 GX ...of kNN synthesized for FPGA had better ...
68
Nearest Neighbor Voting in High Dimensional Data: Learning from Past Occurrences
... The k-nearest neighbor method is among the most influential approaches in machine learning, due to its simplicity and effectiveness. Many extensions to the basic method have been proposed, dealing with various different ...
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