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Tesi sul tema "K-nearest-neighbor"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 25 luglio 2025

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1

Gupta, Nidhi. "Mutual k Nearest Neighbor based Classifier." University of Cincinnati / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1289937369.

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2

Olsson, Christoffer. "Love Thy Neighbor : The Connectivity of the k-nearest Neighbor Graph." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-149639.

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The topic of this thesis is the connectivity of the k-nearest neighbor random geometric graph model. The main result is an expository proof of the fact that there is a critical constant for connectivity. In addition to this, other results related to the connectivity of the k-nearest neighbor model, as well as the closely related Gilbert disc model, are discussed.<br>Denna uppsats fördjupar sig i "the k-nearest neighbor graph", en geometrisk slumpgraf, och när den är sammanhängande. Huvudresultatet är ett förklarande bevis av att det finns en kritisk konstant för egenskapen att vara sammanhänga

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3

Dixit, Siddharth. "Density Based Clustering using Mutual K-Nearest Neighbors." University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1447690719.

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4

Chanzy, Philippe. "Range search and nearest neighbor search in k-d trees." Thesis, McGill University, 1993. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=68164.

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This thesis presents an analysis of the expected complexity of range searching and nearest neighbor searching in random 2-d trees. We show that range searching in a random rectangle $ Delta sb{x} times Delta sb{y}$ can be done in $O lbrack Delta sb{x} Delta sb{y} n+( Delta sb{x}+ Delta sb{y}) n sp alpha +{ rm ln} n rbrack$ expected time. A matching lower bound is also obtained. We also show that nearest neighbor searching in random 2-d trees by any algorithm must take time bounded by $ Omega lbrack n sp{ alpha-1/2}/({ rm ln} n) sp alpha rbrack$ where $ alpha=( sqrt{17}-3)/2$. This disproves a

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5

Kuhlman, Caitlin Anne. "Pivot-based Data Partitioning for Distributed k Nearest Neighbor Mining." Digital WPI, 2017. https://digitalcommons.wpi.edu/etd-theses/1212.

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This thesis addresses the need for a scalable distributed solution for k-nearest-neighbor (kNN) search, a fundamental data mining task. This unsupervised method poses particular challenges on shared-nothing distributed architectures, where global information about the dataset is not available to individual machines. The distance to search for neighbors is not known a priori, and therefore a dynamic data partitioning strategy is required to guarantee that exact kNN can be found autonomously on each machine. Pivot-based partitioning has been shown to facilitate bounding of partitions, however st

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6

Wong, Wing Sing. "K-nearest-neighbor queries with non-spatial predicates on range attributes /." View abstract or full-text, 2005. http://library.ust.hk/cgi/db/thesis.pl?COMP%202005%20WONGW.

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7

CALENDER, CHRISTOPHER R. "APPROXIMATE N-NEAREST NEIGHBOR CLUSTERING ON DISTRIBUTED DATABASES USING ITERATIVE REFINEMENT." University of Cincinnati / OhioLINK, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1092929952.

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8

Aikes, Junior Jorge. "Estudo da influência de diversas medidas de similaridade na previsão de séries temporais utilizando o algoritmo KNN-TSP." Universidade Estadual do Oeste do Parana, 2012. http://tede.unioeste.br:8080/tede/handle/tede/1084.

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Made available in DSpace on 2017-07-10T17:11:50Z (GMT). No. of bitstreams: 1 JORGE AIKES JUNIOR.PDF: 2050278 bytes, checksum: f5bae18bbcb7465240488c45b2c813e7 (MD5) Previous issue date: 2012-04-11<br>Time series can be understood as any set of observations which are time ordered. Among the many possible tasks appliable to temporal data, one that has attracted increasing interest, due to its various applications, is the time series forecasting. The k-Nearest Neighbor - Time Series Prediction (kNN-TSP) algorithm is a non-parametric method for forecasting time series. One of its advantages, i

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9

Ozsakabasi, Feray. "Classification Of Forest Areas By K Nearest Neighbor Method: Case Study, Antalya." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12609548/index.pdf.

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Among the various remote sensing methods that can be used to map forest areas, the K Nearest Neighbor (KNN) supervised classification method is becoming increasingly popular for creating forest inventories in some countries. In this study, the utility of the KNN algorithm is evaluated for forest/non-forest/water stratification. Antalya is selected as the study area. The data used are composed of Landsat TM and Landsat ETM satellite images, acquired in 1987 and 2002, respectively, SRTM 90 meters digital elevation model (DEM) and land use data from the year 2003. The accuracies of different modi

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10

Forsberg, Tom-Henrik, and Johan Sundström. "A comparative study of k nearest neighbor computations on GPUs and CPUs." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-208362.

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The problem of nearest neighbors search arises in many areas of computer science. This search could see a performance boost if implemented on a GPU, utilizing its multithreading capabilities, compared to the sequential execution on a CPU. The purpose of this report is to invesigate how a simple GPU implementation of k nearest neighbors search compares to other common algorithms on a CPU. A brute force search on the GPU was implemented using NVIDIAs CUDA platform, and its performance was tested and compared to implementations from an existing library of both exact brute force search and approxi

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11

Galdames, Patricio A. "Managing continuous k-nearest neighbor queries in mobile peer-to-peer networks." [Ames, Iowa : Iowa State University], 2008.

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12

Jamal, Majd. "Using K-Nearest-Neighbor with valuation metrics to detect similarities between stock performances." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-281962.

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Algorithmic trading has increased in popularity since the publication of Agent-Human Interactions in the Continuous Double Auction by IBM researchers Das et al. (2001). Today many investors acquire algorithms that act on their behalf on the stock markets. Most of the algorithms have worked on predicting stock prices and making transactions when price thresholds are triggered. This project has a different objective and aims to construct a machine learning algorithm to cluster stocks with similar stock performances, and ultimately test the possibility if such stocks continue to perform similarly

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13

Kharsikar, Saket. "A GENE ONTOLOGY BASED COMPUTATIONAL APPROACH FOR THE PREDICTION OF PROTEIN FUNCTIONS." University of Akron / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=akron1187026388.

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Souza, Cristiano Antonio de. "Método híbrido de detecção de intrusão aplicando inteligência artificial." Universidade Estadual do Oeste do Paraná, 2018. http://tede.unioeste.br/handle/tede/3534.

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Submitted by Miriam Lucas (miriam.lucas@unioeste.br) on 2018-04-06T14:31:39Z No. of bitstreams: 2 Cristiano_Antonio_de_Souza_2018.pdf: 2020023 bytes, checksum: 1105b369d497031759e007333c20cad9 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)<br>Made available in DSpace on 2018-04-06T14:31:39Z (GMT). No. of bitstreams: 2 Cristiano_Antonio_de_Souza_2018.pdf: 2020023 bytes, checksum: 1105b369d497031759e007333c20cad9 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2018-02-09<br>Coordenação de Aperfeiçoamento de Pessoal

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15

Rudin, Pierre. "Football result prediction using simple classification algorithms, a comparison between k-Nearest Neighbor and Linear Regression." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-187659.

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Ever since humans started competing with each other, people have tried to accurately predict the outcome of such events. Football is no exception to this and is extra interesting as subject for a project like this with the ever growing amount of data gathered from matches these days. Previously predictors had to make there predictions using there own knowledge and small amounts of data. This report will use this growing amount of data and find out if it is possible to accurately predict the outcome of a football match using the k-Nearest Neighbor algorithm and Linear regression. The algorithms

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16

Neo, TohKoon. "A Direct Algorithm for the K-Nearest-Neighbor Classifier via Local Warping of the Distance Metric." Diss., CLICK HERE for online access, 2007. http://contentdm.lib.byu.edu/ETD/image/etd2168.pdf.

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Neo, Toh Koon Charlie. "A direct boosting algorithm for the k-nearest neighbor classifier via local warping of the distance metric /." Diss., CLICK HERE for online access, 2007. http://contentdm.lib.byu.edu/ETD/image/etd2168.pdf.

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18

Liu, Dongqing. "GENETIC ALGORITHMS FOR SAMPLE CLASSIFICATION OF MICROARRAY DATA." University of Akron / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=akron1125253420.

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19

Zhang, Xianjie, and Sebastian Bogic. "Datautvinning av klickdata : Kombination av klustring och klassifikation." Thesis, KTH, Hälsoinformatik och logistik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-230630.

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Ägare av webbplatser och applikationer tjänar ofta på att användare klickar på deras länkar. Länkarna kan bland annat vara reklam eller varor som säljs. Det finns många studier inom dataanalys angående om en sådan länk kommer att bli klickad, men få studier fokuserar på hur länkarna kan justeras för att bli klickade. Problemet som företaget Flygresor.se har är att de saknar ett verktyg för deras kunder, resebyråer, att analysera deras biljetter och därefter justera attributen för resorna. Den efterfrågade lösningen var en applikation som gav förslag på hur biljetterna skulle förändras för att

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20

Karginova, Nadezda. "Identification of Driving Styles in Buses." Thesis, Halmstad University, Intelligent systems (IS-lab), 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-4830.

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<p>It is important to detect faults in bus details at an early stage. Because the driving style affects the breakdown of different details in the bus, identification of the driving style is important to minimize the number of failures in buses.</p><p>The identification of the driving style of the driver was based on the input data which contained examples of the driving runs of each class. K-nearest neighbor and neural networks algorithms were used. Different models were tested.</p><p>It was shown that the results depend on the selected driving runs. A hypothesis was suggested that the example

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21

Pathirana, Vindya Kumari. "Nearest Neighbor Foreign Exchange Rate Forecasting with Mahalanobis Distance." Scholar Commons, 2015. http://scholarcommons.usf.edu/etd/5757.

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Foreign exchange (FX) rate forecasting has been a challenging area of study in the past. Various linear and nonlinear methods have been used to forecast FX rates. As the currency data are nonlinear and highly correlated, forecasting through nonlinear dynamical systems is becoming more relevant. The nearest neighbor (NN) algorithm is one of the most commonly used nonlinear pattern recognition and forecasting methods that outperforms the available linear forecasting methods for the high frequency foreign exchange data. The basic idea behind the NN is to capture the local behavior of the data by

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22

Mao, Qian. "Clusters Identification: Asymmetrical Case." Thesis, Uppsala universitet, Informationssystem, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-208328.

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Cluster analysis is one of the typical tasks in Data Mining, and it groups data objects based only on information found in the data that describes the objects and their relationships. The purpose of this thesis is to verify a modified K-means algorithm in asymmetrical cases, which can be regarded as an extension to the research of Vladislav Valkovsky and Mikael Karlsson in Department of Informatics and Media. In this thesis an experiment is designed and implemented to identify clusters with the modified algorithm in asymmetrical cases. In the experiment the developed Java application is based

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Mestre, Ricardo Jorge Palheira. "Improvements on the KNN classifier." Master's thesis, Faculdade de Ciências e Tecnologia, 2013. http://hdl.handle.net/10362/10923.

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática<br>The object classification is an important area within the artificial intelligence and its application extends to various areas, whether or not in the branch of science. Among the other classifiers, the K-nearest neighbor (KNN) is among the most simple and accurate especially in environments where the data distribution is unknown or apparently not parameterizable. This algorithm assigns the classifying element the major class in the K nearest neighbors. According to the original algorithm, this classification implies the

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24

Maitaria, Kazungu. "ENABLING HYDROLOGICAL INTERPRETATION OF MONTHLY TO SEASONAL PRECIPITATION FORECASTS IN THE CORE NORTH AMERICAN MONSOON REGION." Diss., The University of Arizona, 2009. http://hdl.handle.net/10150/193926.

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The aim of the research undertaken in this dissertation was to use medium-range to seasonal precipitation forecasts for hydrologic applications for catchments in the core North American Monsoon (NAM) region. To this end, it was necessary to develop a better understanding of the physical and statistical relationships between runoff processes and the temporal statistics of rainfall. To achieve this goal, development of statistically downscaled estimates of warm season precipitation over the core region of the North American Monsoon Experiment (NAME) were developed. Currently, NAM precipitation i

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25

Silva, Eliezer de Souza da 1988. "Metric space indexing for nearest neighbor search in multimedia context : Indexação de espaços métricos para busca de vizinho mais próximo em contexto multimídia." [s.n.], 2014. http://repositorio.unicamp.br/jspui/handle/REPOSIP/258942.

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Orientador: Eduardo Alves do Valle Junior<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação<br>Made available in DSpace on 2018-08-26T08:10:33Z (GMT). No. of bitstreams: 1 Silva_EliezerdeSouzada_M.pdf: 2350845 bytes, checksum: dd31928bd19312563101a08caea74d63 (MD5) Previous issue date: 2014<br>Resumo: A crescente disponibilidade de conteúdo multimídia é um desafio para a pesquisa em Recuperação de Informação. Usuários querem não apenas ter acesso aos documentos multimídia, mas também obter semântica destes documentos, de modo que

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26

Torres, Winnie de Lima. "Detecção de desvios vocais utilizando modelos auto regressivos e o algoritmo KNN." PROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA ELÉTRICA E DE COMPUTAÇÃO, 2018. https://repositorio.ufrn.br/jspui/handle/123456789/25105.

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Submitted by Automação e Estatística (sst@bczm.ufrn.br) on 2018-05-02T22:45:42Z No. of bitstreams: 1 WinnieDeLimaTorres_DISSERT.pdf: 1538022 bytes, checksum: ad6fc16589291a27b8b718b755afdf44 (MD5)<br>Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2018-05-07T21:40:35Z (GMT) No. of bitstreams: 1 WinnieDeLimaTorres_DISSERT.pdf: 1538022 bytes, checksum: ad6fc16589291a27b8b718b755afdf44 (MD5)<br>Made available in DSpace on 2018-05-07T21:40:35Z (GMT). No. of bitstreams: 1 WinnieDeLimaTorres_DISSERT.pdf: 1538022 bytes, checksum: ad6fc16589291a27b8b718b

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Agarwal, Akrita. "Exploring the Noise Resilience of Combined Sturges Algorithm." University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1447070335.

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Prabhu, Chitra. "COMPARISON OF THE UTILITY OF REGRESSION ANALYSIS AND K-NEAREST NEIGHBOR TECHNIQUE TO ESTIMATE ABOVE-GROUND BIOMASS IN PINE FORESTS USING LANDSAT ETM+ IMAGERY." MSSTATE, 2006. http://sun.library.msstate.edu/ETD-db/theses/available/etd-08092006-091449/.

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There is a lack of precise and universally accepted approach in the quantification of carbon sequestered in aboveground woody biomass using remotely sensed data. Drafting of the Kyoto Protocol has made the subject of carbon sequestration more important, making the development of accurate and cost-effective remote sensing models a necessity. There has been much work done in estimating aboveground woody biomass from spectral data using the traditional multiple linear regression analysis approach and the Finnish k-nearest neighbor approach, but the accuracy of these methods to estimate biomass ha

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29

Gard, Rikard. "Design-based and Model-assisted estimators using Machine learning methods : Exploring the k-Nearest Neighbor metod applied to data from the Recreational Fishing Survey." Thesis, Örebro universitet, Handelshögskolan vid Örebro Universitet, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-72488.

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Amlathe, Prakhar. "Standard Machine Learning Techniques in Audio Beehive Monitoring: Classification of Audio Samples with Logistic Regression, K-Nearest Neighbor, Random Forest and Support Vector Machine." DigitalCommons@USU, 2018. https://digitalcommons.usu.edu/etd/7050.

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Honeybees are one of the most important pollinating species in agriculture. Every three out of four crops have honeybee as their sole pollinator. Since 2006 there has been a drastic decrease in the bee population which is attributed to Colony Collapse Disorder(CCD). The bee colonies fail/ die without giving any traditional health symptoms which otherwise could help in alerting the Beekeepers in advance about their situation. Electronic Beehive Monitoring System has various sensors embedded in it to extract video, audio and temperature data that could provide critical information on colony beha

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Trad, Riadh. "Découverte d'évènements par contenu visuel dans les médias sociaux." Thesis, Paris, ENST, 2013. http://www.theses.fr/2013ENST0030/document.

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L’évolution du web, de ce qui était typiquement connu comme un moyen de communication à sens unique en mode conversationnel, a radicalement changé notre manière de traiter l’information. Des sites de médias sociaux tels que Flickr et Facebook, offrent des espaces d’échange et de diffusion de l’information. Une information de plus en plus riche, mais aussi personnelle, et qui s’organise, le plus souvent, autour d’événements de la vie réelle. Ainsi, un événement peut être perçu comme un ensemble de vues personnelles et locales, capturées par différents utilisateurs. Identifier ces différentes in

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32

Mazzara, Gloria Patrika. "Brain tumor target volume determination for radiation therapy treatment planning through the use of automated MRI segmentation." [Tampa, Fla.] : University of South Florida, 2004. http://purl.fcla.edu/fcla/etd/SFE0000600.

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Tsipenyuk, Gregory. "Evaluation of decentralized email architecture and social network analysis based on email attachment sharing." Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/273963.

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Present day email is provided by centralized services running in the cloud. The services transparently connect users behind middleboxes and provide backup, redundancy, and high availability at the expense of user privacy. In present day mobile environments, users can access and modify email from multiple devices with updates reconciled on the central server. Prioritizing updates is difficult and may be undesirable. Moreover, legacy email protocols do not provide optimal email synchronization and access. Recent phenomena of the Internet of Things (IoT) will see the number of interconnected devi

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Favaro, Martha Maria Andreotti 1981. "Exploração de dados multivariados de fontes e extratos de antocianinas ultilizando análise de componentes princiaipais e método do vizinho mais proximo." [s.n.], 2012. http://repositorio.unicamp.br/jspui/handle/REPOSIP/250159.

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Orientador: Adriana Vitorino Rossi<br>Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Química<br>Made available in DSpace on 2018-08-20T02:46:28Z (GMT). No. of bitstreams: 1 Favaro_MarthaMariaAndreotti_D.pdf: 3734314 bytes, checksum: 08002efe51b2f18e9a942c3b818270b7 (MD5) Previous issue date: 2012<br>Resumo: Antocianinas (ACYS) são corantes naturais responsáveis pela coloração de frutas, hortaliças, flores e grãos. Novas perspectivas de usos de antocianinas em diversos segmentos industriais estimulam estudos analíticos para sistematizar a identificação e a classificação de

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Гавриленко, Р. А. "Інформаційна технологія розпізнавання символьних образів на прикладі реалізації чат-боту для соціальної платформи". Master's thesis, Сумський державний університет, 2018. http://essuir.sumdu.edu.ua/handle/123456789/72312.

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Hallström, Per, and Per Dellrup. "Improving WiFi positioning through the use of successive in-sequence signal strength samples." Thesis, Växjö University, School of Mathematics and Systems Engineering, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:vxu:diva-590.

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<p>As portable computers and wireless networks are becoming ubiquitous, it is natural to consider the user’s position as yet another aspect to take into account when providing services that are tailored to meet the needs of the consumers. Location aware systems could guide persons through buildings, to a particular bookshelf in a library or assist in a vast variety of other applications that can benefit from knowing the user’s position.</p><p>In indoor positioning systems, the most commonly used method for determining the location is to collect samples of the strength of the received signal fr

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Guzman, Esteban. "Generating Exploration Mission-3 Trajectories to a 9:2 NRHO using Machine Learning." DigitalCommons@CalPoly, 2018. https://digitalcommons.calpoly.edu/theses/1953.

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The purpose of this thesis is to design a machine learning algorithm platform that provides expanded knowledge of mission availability through a launch season by improving trajectory resolution and introducing launch mission forecasting. The specific scenario addressed in this paper is one in which data is provided for four deterministic translational maneuvers through a mission to a Near Rectilinear Halo Orbit (NRHO) with a 9:2 synodic frequency. Current launch availability knowledge under NASA’s Orion Orbit Performance Team is established by altering optimization variables associated to give

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38

Bertilsson, Tobias, and Romario Johansson. "Undersökning om hjulmotorströmmar kan användas som alternativ metod för kollisiondetektering i autonoma gräsklippare. : Klassificering av hjulmotorströmmar med KNN och MLP." Thesis, Tekniska Högskolan, Högskolan i Jönköping, JTH, Datateknik och informatik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-43555.

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Purpose – The purpose of the study is to expand the knowledge of how wheel motor currents can be combined with machine learning to be used in a collision detection system for autonomous robots, in order to decrease the number of external sensors and open new design opportunities and lowering production costs. Method – The study is conducted with design science research where two artefacts are developed in a cooperation with Globe Tools Group. The artefacts are evaluated in how they categorize data given by an autonomous robot in the two categories collision and non-collision. The artefacts are

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Holsbach, Nicole. "Método de mineração de dados para diagnóstico de câncer de mama baseado na seleção de variáveis." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2012. http://hdl.handle.net/10183/76183.

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A presente dissertação propõe métodos para mineração de dados para diagnóstico de câncer de mama (CM) baseado na seleção de variáveis. Partindo-se de uma revisão sistemática, sugere-se um método para a seleção de variáveis para classificação das observações (pacientes) em duas classes de resultado, benigno ou maligno, baseado na análise citopatológica de amostras de célula da mama de pacientes. O método de seleção de variáveis para categorização das observações baseia-se em 4 passos operacionais: (i) dividir o banco de dados original em porções de treino e de teste, e aplicar a ACP (Análise de

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Narreddy, Naga Sambu Reddy, and Tuğrul Durgun. "Clusters (k) Identification without Triangle Inequality : A newly modelled theory." Thesis, Uppsala universitet, Institutionen för informatik och media, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-183608.

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Cluster analysis characterizes data that are similar enough and useful into meaningful groups (clusters).For example, cluster analysis can be applicable to find group of genes and proteins that are similar, to retrieve information from World Wide Web, and to identify locations that are prone to earthquakes. So the study of clustering has become very important in several fields, which includes psychology and other social sciences, biology, statistics, pattern recognition, information retrieval, machine learning and data mining [1] [2]. Cluster analysis is the one of the widely used technique

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Jiao, Lianmeng. "Classification of uncertain data in the framework of belief functions : nearest-neighbor-based and rule-based approaches." Thesis, Compiègne, 2015. http://www.theses.fr/2015COMP2222/document.

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Dans de nombreux problèmes de classification, les données sont intrinsèquement incertaines. Les données d’apprentissage disponibles peuvent être imprécises, incomplètes, ou même peu fiables. En outre, des connaissances spécialisées partielles qui caractérisent le problème de classification peuvent également être disponibles. Ces différents types d’incertitude posent de grands défis pour la conception de classifieurs. La théorie des fonctions de croyance fournit un cadre rigoureux et élégant pour la représentation et la combinaison d’une grande variété d’informations incertaines. Dans cette thè

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Forsman, Robin, and Jimmy Jönsson. "Artificial intelligence and Machine learning : a diabetic readmission study." Thesis, Högskolan Kristianstad, Avdelningen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hkr:diva-19412.

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The maturing of Artificial intelligence provides great opportunities for healthcare, but also comes with new challenges. For Artificial intelligence to be adequate a comprehensive analysis of the data is necessary along with testing the data in multiple algorithms to determine which algorithm is appropriate to use. In this study collection of data has been gathered that consists of patients who have either been readmitted or not readmitted to hospital within 30-days after being admitted. The data has then been analyzed and compared in different algorithms to determine the most appropriate algo

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Zapletal, Petr. "Klasifikační metody analýzy vrstvy nervových vláken na sítnici." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2010. http://www.nusl.cz/ntk/nusl-218575.

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This thesis is deal with classification for retinal nerve fibre layer. Texture features from six texture analysis methods are used for classification. All methods calculate feature vector from inputs images. This feature vector is characterized for every cluster (class). Classification is realized by three supervised learning algorithms and one unsupervised learning algorithm. The first testing algorithm is called Ho-Kashyap. The next is Bayess classifier NDDF (Normal Density Discriminant Function). The third is the Nearest Neighbor algorithm k-NN and the last tested classifier is algorithm K-

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Oliveira, Willian Dener de. "Operação de busca exata aos K-vizinhos mais próximos reversos em espaços métricos." Universidade de São Paulo, 2010. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-17052010-163917/.

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A complexidade dos dados armazenados em grandes bases de dados aumenta cada vez mais, criando a necessidade de novas operações de consulta. Uma classe de operações que tem apresentado interesse crescente são as chamadas Consultas por Similaridade, sendo as mais conhecidas as consultas por Abrangência (\'R IND. q\') e por k-Vizinhos mais Proximos (kNN), sendo que esta ultima obtem quais são os k elementos armazenados mais similares a um dado elemento de referência. Outra consulta que é interessante tanto para consultas diretas quanto como parte de operações de análises mais complexas e a operaç

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Curtin, Ryan Ross. "Improving dual-tree algorithms." Diss., Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/54354.

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This large body of work is entirely centered around dual-tree algorithms, a class of algorithm based on spatial indexing structures that often provide large amounts of acceleration for various problems. This work focuses on understanding dual-tree algorithms using a new, tree-independent abstraction, and using this abstraction to develop new algorithms. Stated more clearly, the thesis of this entire work is that we may improve and expand the class of dual-tree algorithms by focusing on and providing improvements for each of the three independent components of a dual-tree algorithm: the type o

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Janson, Lisa, and Minna Mathisson. "Data mining inom tillverkningsindustrin : En fallstudie om möjligheten att förutspå kvalitetsutfall i produktionslinjer." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-301246.

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I detta arbete har en fallstudie utförts på Volvo Group i Köping. I takt med ¨övergången till industri 4.0, ökar möjligheterna att använda maskininlärning som ett verktyg i analysen av industriell data och vidareutvecklingen av industriproduktionen. Detta arbete syftar till att undersöka möjligheten att förutspå kvalitetsutfall vid sammanpressning av nav och huvudaxel. Metoden innefattar implementering av tre maskininlärningsmodeller samt evaluering av dess prestation i förhållande till varandra. Vid applicering av modellerna på monteringsdata från fabriken erhölls ett bristfälligt resultat, v

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Trad, Riadh. "Découverte d'évènements par contenu visuel dans les médias sociaux." Electronic Thesis or Diss., Paris, ENST, 2013. http://www.theses.fr/2013ENST0030.

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L’évolution du web, de ce qui était typiquement connu comme un moyen de communication à sens unique en mode conversationnel, a radicalement changé notre manière de traiter l’information. Des sites de médias sociaux tels que Flickr et Facebook, offrent des espaces d’échange et de diffusion de l’information. Une information de plus en plus riche, mais aussi personnelle, et qui s’organise, le plus souvent, autour d’événements de la vie réelle. Ainsi, un événement peut être perçu comme un ensemble de vues personnelles et locales, capturées par différents utilisateurs. Identifier ces différentes in

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Björk, Gabriella. "Evaluation of system design strategies and supervised classification methods for fruit recognition in harvesting robots." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-217859.

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This master thesis project is carried out by one student at the Royal Institute of Technology in collaboration with Cybercom Group. The aim was to evaluate and compare system design strategies for fruit recognition in harvesting robots and the performance of supervised machine learning classification methods when applied to this specific task. The thesis covers the basics of these systems; to which parameters, constraints, requirements, and design decisions have been investigated. The framework is used as a foundation for the implementation of both sensing system, and processing and classifica

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Gu, Yu-Jia, and 古祐嘉. "Adaptive K-Nearest Neighbor Algorithm." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/35887089581319797969.

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碩士<br>元智大學<br>資訊管理學系<br>97<br>The K-nearest-neighbor algorithm traditionally predicts the class of a record based on the decision from the K nearest neighbors of the record, for a fixed K value. However, recent studies showed that using different K values for different records could improve the prediction accuracy. This study integrates Fuzzy C-means algorithm to assist determining a proper K value for each record in a local KNN algorithm. Performance results show this method outperforms the traditional KNN in term of prediction accuracy.

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Chen, Chien Hung, and 陳建宏. "On The Edited Fuzzy K-Nearest Neighbor Rule." Thesis, 1995. http://ndltd.ncl.edu.tw/handle/29870031805192232850.

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碩士<br>中原大學<br>應用數學研究所<br>83<br>In pattern classification, the k nearest neighbor rule (k-NNR) is a well-known nonparametric decision rule. Fuzzy sets originated by Zadeh(1965) gave an idea of uncertainty of belongingness that is described by a membership function.The fuzzy k-NNR has been proposed by many researchers and has been proved to have better performance than k-NNR.Wilson (1972) proposed an edited k-NNR to improve its performance by using an editing procedure to reduce the number of

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