Relevant bibliographies by topics / Decision tree classifier / Dissertations / Theses
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Dissertations / Theses on the topic 'Decision tree classifier'

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Published: 4 June 2021
Last updated: 25 July 2025

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1

Ardeshir, G. "Decision tree simplification for classifier ensembles." Thesis, University of Surrey, 2002. http://epubs.surrey.ac.uk/843022/.

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Design of ensemble classifiers involves three factors: 1) a learning algorithm to produce a classifier (base classifier), 2) an ensemble method to generate diverse classifiers, and 3) a combining method to combine decisions made by base classifiers. With regard to the first factor, a good choice for constructing a classifier is a decision tree learning algorithm. However, a possible problem with this learning algorithm is its complexity which has only been addressed previously in the context of pruning methods for individual trees. Furthermore, the ensemble method may require the learning algo
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2

Rosten, David Paul 1967. "Automatic design of a decision tree classifier employing neural networks." Thesis, The University of Arizona, 1991. http://hdl.handle.net/10150/277881.

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Pattern recognition problems involve two main issues: feature formulation and classifier design. This thesis is concerned with the latter. Numerous algorithms for the design of pattern recognition systems have been published, and the algorithm detailed herein is a new approach--specific to the design of decision tree classifiers. It involves a top-down strategy, optimizing the root node decision and then subsequently its children. To assess various pattern space partitions, the Tie statistical distance measure quantified the separability of potential cluster groupings. Additionally, a separate
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Thomas, Clifford S. "From 'tree' based Bayesian networks to mutual information classifiers : deriving a singly connected network classifier using an information theory based technique." Thesis, University of Stirling, 2005. http://hdl.handle.net/1893/2623.

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For reasoning under uncertainty the Bayesian network has become the representation of choice. However, except where models are considered 'simple' the task of construction and inference are provably NP-hard. For modelling larger 'real' world problems this computational complexity has been addressed by methods that approximate the model. The Naive Bayes classifier, which has strong assumptions of independence among features, is a common approach, whilst the class of trees is another less extreme example. In this thesis we propose the use of an information theory based technique as a mechanism f
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STEFFENINO, SARA. "Urban land cover mapping using medium spatial resolution satellite imageries: effectiveness of Decision Tree Classifier." Doctoral thesis, Politecnico di Torino, 2013. http://hdl.handle.net/11583/2507348.

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The study is inserted in the framework of information extraction from satellite imageries for supporting rapid mapping activities, where information need to be extracted quickly and the elimination, also if partially, of manual digitalization procedures, can be considered a great breakthrough. The main aim of this study was therefore to develop algorithms for the extraction of urban layer by means of medium spatial resolution Landsat data processing; Decision Tree classifier was investigated as classification techniques, thus it allows to extract rules that can be later applied to different
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ARELLANO-NERI, OLIMPIA. "AN IMPROVED METHODOLOGY FOR LAND-COVER CLASSIFICATION USING ARTIFICIAL NEURAL NETWORKS AND A DECISION TREE CLASSIFIER." University of Cincinnati / OhioLINK, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1085589862.

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Boujari, Tahereh. "Instance-based ontology alignment using decision trees." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-84918.

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Using ontologies is a key technology in the semantic web. The semantic web helps people to store their data on the web, build vocabularies, and has written rules for handling these data and also helps the search engines to distinguish between the information they want to access in web easier. In order to use multiple ontologies created by different experts we need matchers to find the similar concepts in them to use it to merge these ontologies. Text based searches use the string similarity functions to find the equivalent concepts inside ontologies using their names.This is the method that is
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Zhong, Mingyu. "AN ANALYSIS OF MISCLASSIFICATION RATES FOR DECISION TREES." Doctoral diss., University of Central Florida, 2007. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/2496.

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The decision tree is a well-known methodology for classification and regression. In this dissertation, we focus on the minimization of the misclassification rate for decision tree classifiers. We derive the necessary equations that provide the optimal tree prediction, the estimated risk of the tree's prediction, and the reliability of the tree's risk estimation. We carry out an extensive analysis of the application of Lidstone's law of succession for the estimation of the class probabilities. In contrast to existing research, we not only compute the expected values of the risks but also calcul
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Jia, Xiuping Electrical Engineering Australian Defence Force Academy UNSW. "Classification techniques for hyperspectral remote sensing image data." Awarded by:University of New South Wales - Australian Defence Force Academy. School of Electrical Engineering, 1996. http://handle.unsw.edu.au/1959.4/38713.

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Hyperspectral remote sensing image data, such as that recorded by AVIRIS with 224 spectral bands, provides rich information on ground cover types. However, it presents new problems in machine assisted interpretation, mainly in long processing times and the difficulties of class training due to the low ratio of number of training samples to the number of bands. This thesis investigates feasible and efficient feature reduction and image classification techniques which are appropriate for hyperspectral image data. The study is reported in three parts. The first concerns a deterministic approach
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9

Benda, Ondřej. "Návrh rozhodovacích stromů na základě evolučních algoritmů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219457.

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Tato diplomová práce pojednává o dvou algoritmech pro dolování z proudu dat - Very Fast Decision Tree (VFDT) a Concept-adapting Very Fast Decision Tree (CVFDT). Je vysvětlen princip klasifikace rozhodovacím stromem. Je popsána základní myšlenka konstrukce stromu Hoeffding Tree, který je základem pro algoritmy VFDT a CVFDT. Tyto algoritmy jsou poté rozebrány detailněji. Dále se tato práce zabývá návrhem algoritmu Genetického Programování (GP), který je použit pro vytváření klasifikátoru obrazových dat. Vytvořený klasifikátor je použit jako alternativní způsob klasifikace objektů v obraze ve fra
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Федоров, Д. П. "Comparison of classifiers based on the decision tree." Thesis, ХНУРЕ, 2021. https://openarchive.nure.ua/handle/document/16430.

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The main purpose of this work is to compare classifiers. Random Forest and XGBoost are two popular machine learning algorithms. In this paper, we looked at how they work, compared their features, and obtained accurate results from their robots.
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Igboamalu, Frank Nonso. "Decision tree classifiers for incident call data sets." Master's thesis, University of Cape Town, 2017. http://hdl.handle.net/11427/27076.

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Information technology (IT) has become one of the key technologies for economic and social development in any organization. Therefore the management of Information technology incidents, and particularly in the area of resolving the problem very fast, is of concern to Information technology managers. Delays can result when incorrect subjects are assigned to Information technology incident calls: because the person sent to remedy the problem has the wrong expertise or has not brought with them the software or hardware they need to help that user. In the case study used for this work, there are n
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12

Feray, Nicolas. "Reconnaissance de formes : application aux chiffres manuscrits." Rouen, 1995. http://www.theses.fr/1995ROUES028.

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Cette thèse traite de la reconnaissance des chiffres manuscrits hors lignes. Le système de reconnaissance propose est constitué de deux classifieurs fondamentalement différents. Les chapitres 3, 4 et 5 sont consacrés à l'étude du premier classifieur. Celui-ci analyse l'image du chiffre à reconnaître par l'intermédiaire de considérations locales sur sa forme. C'est pourquoi, nous qualifions de vision locale le mécanisme de perception du chiffre. Le choix des primitives et leur exploitation séquentielle par un arbre de décision sont rigoureux et basés sur le concept de l'information transmise pa
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Bogdan, Vukobratović. "Hardware Acceleration of Nonincremental Algorithms for the Induction of Decision Trees and Decision Tree Ensembles." Phd thesis, Univerzitet u Novom Sadu, Fakultet tehničkih nauka u Novom Sadu, 2017. https://www.cris.uns.ac.rs/record.jsf?recordId=102520&source=NDLTD&language=en.

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The thesis proposes novel full decision tree and decision tree ensembleinduction algorithms EFTI and EEFTI, and various possibilities for theirimplementations are explored. The experiments show that the proposed EFTIalgorithm is able to infer much smaller DTs on average, without thesignificant loss in accuracy, when compared to the top-down incremental DTinducers. On the other hand, when compared to other full tree inductionalgorithms, it was able to produce more accurate DTs, with similar sizes, inshorter times. Also, the hardware architectures for acceleration of thesealgorithms (EFTIP and E
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Guňka, Jiří. "Adaptivní klient pro sociální síť Twitter." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2011. http://www.nusl.cz/ntk/nusl-237052.

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The goal of this term project is create user friendly client of Twitter. They may use methods of machine learning as naive bayes classifier to mentions new interests tweets. For visualissation this tweets will be use hyperbolic trees and some others methods.
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LOPES, Marcus Vinicius de Sousa. "Aplicação de classificadores para determinação de conformidade de biodiesel." Universidade Federal do Maranhão, 2017. http://tedebc.ufma.br:8080/jspui/handle/tede/1896.

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Submitted by Rosivalda Pereira (mrs.pereira@ufma.br) on 2017-09-04T17:47:07Z No. of bitstreams: 1 MarcusLopes.pdf: 2085041 bytes, checksum: 14f6f9bbe0d5b050a23103874af8c783 (MD5)<br>Made available in DSpace on 2017-09-04T17:47:07Z (GMT). No. of bitstreams: 1 MarcusLopes.pdf: 2085041 bytes, checksum: 14f6f9bbe0d5b050a23103874af8c783 (MD5) Previous issue date: 2017-07-26<br>The growing demand for energy and the limitations of oil reserves have led to the search for renewable and sustainable energy sources to replace, even partially, fossil fuels. Biodiesel has become in last decades the ma
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Chrysostomou, Kyriacos. "The role of classifiers in feature selection : number vs nature." Thesis, Brunel University, 2008. http://bura.brunel.ac.uk/handle/2438/3038.

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Wrapper feature selection approaches are widely used to select a small subset of relevant features from a dataset. However, Wrappers suffer from the fact that they only use a single classifier when selecting the features. The problem of using a single classifier is that each classifier is of a different nature and will have its own biases. This means that each classifier will select different feature subsets. To address this problem, this thesis aims to investigate the effects of using different classifiers for Wrapper feature selection. More specifically, it aims to investigate the effects of
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Gilmore, Eugene M. "Learning Interpretable Decision Tree Classifiers with Human in the Loop Learning and Parallel Coordinates." Thesis, Griffith University, 2022. http://hdl.handle.net/10072/418633.

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The Machine Learning (ML) community has recently started to recognise the importance of model interpretability when using ML techniques. In this work, I review the literature on Explainable Artificial Intelligence (XAI) and interpretability in ML and discuss several reasons why interpretability is critical for many ML applications. Although there is now increased interest in XAI, there are significant issues with the approaches taken in a large portion of the research in XAI. In particular, the popularity of techniques that try to explain black-box models often leads to misleading explanations
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Gangadhara, Kanthi, and Dubbaka Sai Anusha Reddy. "Comparing Compound and Ordinary Diversity measures Using Decision Trees." Thesis, Högskolan i Borås, Institutionen Handels- och IT-högskolan, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-20385.

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An ensemble of classifiers succeeds in improving the accuracy of the whole when thecomponent classifiers are both diverse and accurate. Diversity is required to ensure that theclassifiers make uncorrelated errors. Theoretical and experimental approaches from previousresearch show very low correlation between ensemble accuracy and diversity measure.Introducing Proposed Compound diversity functions by Albert Hung-Ren KO and RobertSabourin, (2009), by combining diversities and performances of individual classifiers exhibitstrong correlations between the diversities and accuracy. To be consistent
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Gamba, Mateus Luiz. "Árvores de decisão como técnica para classificar a resposta quanto à atividade celular in vitro para diferentes tratamentos superficiais em titânio." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2016. http://hdl.handle.net/10183/185825.

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Diversos artigos têm sido publicados a fim de avaliar a influência de diferentes tratamentos de superfície de TiO2/Ti sobre atividade celular de osteoblastos, tentando estabelecer dessa forma a relação entre as propriedades de superfície e o processo de ossointegração. No entanto, ainda existem lacunas críticas na avaliação e compreensão do efeito das propriedades de superfície sobre atividade celular. Como muitos fatores podem influenciar na resposta celular, a avaliação da influência combinada dos diferentes parâmetros empregados dificulta a compreensão do efeito das propriedades superficiai
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20

Polák, Michael Adam. "Identifikace zařízení na základě jejich chování v síti." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2020. http://www.nusl.cz/ntk/nusl-417243.

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Táto práca sa zaoberá problematikou identifikácie sieťových zariadení na základe ich chovania v sieti. S neustále sa zvyšujúcim počtom zariadení na sieti je neustále dôležitejšia schopnosť identifikovať zariadenia z bezpečnostných dôvodov. Táto práca ďalej pojednáva o základoch počítačových sietí a metódach, ktoré boli využívané v minulosti na identifikáciu sieťových zariadení. Následne sú popísané algoritmy využívané v strojovom učení a taktiež sú popísané ich výhody i nevýhody. Nakoniec, táto práca otestuje dva tradičné algorithmy strojového učenia a navrhuje dva nové prístupy na identifikác
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Dočekal, Martin. "Porovnání klasifikačních metod." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2019. http://www.nusl.cz/ntk/nusl-403211.

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This thesis deals with a comparison of classification methods. At first, these classification methods based on machine learning are described, then a classifier comparison system is designed and implemented. This thesis also describes some classification tasks and datasets on which the designed system will be tested. The evaluation of classification tasks is done according to standard metrics. In this thesis is presented design and implementation of a classifier that is based on the principle of evolutionary algorithms.
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Kraus, Michal. "Zjednoznačňování slovních významů." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2008. http://www.nusl.cz/ntk/nusl-235964.

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The master's thesis deals with sense disambiguation of Czech words. Reader is informed about task's history and used algorithms are introduced. There are naive Bayes classifier, AdaBoost classifier, maximum entrophy method and decision trees described in this thesis. Used methods are clearly demonstrated. In the next parts of this thesis are used data also described.  Last part of the thesis describe reached results. There are some ideas to improve the system at the end of the thesis.
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Santos, Cinara de Jesus. "Avaliação do uso de classificadores para verificação de atendimento a critérios de seleção em programas sociais." Universidade Federal de Juiz de Fora (UFJF), 2017. https://repositorio.ufjf.br/jspui/handle/ufjf/5582.

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Submitted by isabela.moljf@hotmail.com (isabela.moljf@hotmail.com) on 2017-08-15T12:01:50Z No. of bitstreams: 1 cinaradejesussantos.pdf: 4566569 bytes, checksum: bddc2ea97276541c0a8ad30a371102d1 (MD5)<br>Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-08-15T12:02:54Z (GMT) No. of bitstreams: 1 cinaradejesussantos.pdf: 4566569 bytes, checksum: bddc2ea97276541c0a8ad30a371102d1 (MD5)<br>Made available in DSpace on 2017-08-15T12:02:54Z (GMT). No. of bitstreams: 1 cinaradejesussantos.pdf: 4566569 bytes, checksum: bddc2ea97276541c0a8ad30a371102d1 (MD5) Pr
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Thomas, Rodney H. "Machine Learning for Exploring State Space Structure in Genetic Regulatory Networks." Diss., NSUWorks, 2018. https://nsuworks.nova.edu/gscis_etd/1053.

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Genetic regulatory networks (GRN) offer a useful model for clinical biology. Specifically, such networks capture interactions among genes, proteins, and other metabolic factors. Unfortunately, it is difficult to understand and predict the behavior of networks that are of realistic size and complexity. In this dissertation, behavior refers to the trajectory of a state, through a series of state transitions over time, to an attractor in the network. This project assumes asynchronous Boolean networks, implying that a state may transition to more than one attractor. The goal of this project is to
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Svoboda, Pavel. "Metody klasifikace www stránek." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2009. http://www.nusl.cz/ntk/nusl-236643.

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The main goal of this master's thesis was to study the main principles of classification methods. Basic principles of knowledge discovery process, data mining and using an external class CSSBox are described. Special attantion was paid to implementation of a ,,k-nearest neighbors`` classification method. The first objective of this work was to create training and testing data described by 'n' attributes. The second objective was to perform experimental analysis to determine a good value for 'k', the number of neighbors.
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Mézl, Martin. "Pokročilé dolování v datech v kardiologii." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2009. http://www.nusl.cz/ntk/nusl-217971.

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The aim of this master´s thesis is to analyse and search unusual dependencies in database of patients from Internal Cardiology Clinic Faculty Hospital Brno. The part of the work is theoretical overview of common data mining methods used in medicine, especially decision trees, naive Bayesian classifier, artificial neural networks and association rules. Looking for unusual dependencies between atributes is realized by association rules and naive Bayesian classifier. The output of this work is a complex system for Knowledge discovery in databases process for any data set. This work was realized w
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Vuk, Vranjković. "Реконфигурабилне архитектуре за хардверску акцелерацију предиктивних модела машинског учења". Phd thesis, Univerzitet u Novom Sadu, Fakultet tehničkih nauka u Novom Sadu, 2015. http://www.cris.uns.ac.rs/record.jsf?recordId=94819&source=NDLTD&language=en.

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У овој дисертацији представљене су универзалне реконфигурабилнеархитектуре грубог степена гранулације за хардверску имплементацијуDT (decision trees), ANN (artificial neural networks) и SVM (support vectormachines) предиктивних модела као и хомогених и хетерогенихансамбала. Коришћењем ових архитектура реализоване су две врстеDT модела, две врсте ANN модела, две врсте SVM модела и седамврста ансамбала на FPGA (field programmable gate arrays) чипу.Експерименти, засновани на скуповима из стандардне UCI базе скуповаза машинско учење, показују да FPGA имплементација омогућавазначајно убрзање (од 1
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Konečný, Antonín. "Využití umělé inteligence v technické diagnostice." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2021. http://www.nusl.cz/ntk/nusl-443221.

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The diploma thesis is focused on the use of artificial intelligence methods for evaluating the fault condition of machinery. The evaluated data are from a vibrodiagnostic model for simulation of static and dynamic unbalances. The machine learning methods are applied, specifically supervised learning. The thesis describes the Spyder software environment, its alternatives, and the Python programming language, in which the scripts are written. It contains an overview with a description of the libraries (Scikit-learn, SciPy, Pandas ...) and methods — K-Nearest Neighbors (KNN), Support Vector Machi
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Mihoub, Alaeddine. "Apprentissage statistique de modèles de comportement multimodal pour les agents conversationnels interactifs." Thesis, Université Grenoble Alpes (ComUE), 2015. http://www.theses.fr/2015GREAT079/document.

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L'interaction face-à-face représente une des formes les plus fondamentales de la communication humaine. C'est un système dynamique multimodal et couplé – impliquant non seulement la parole mais de nombreux segments du corps dont le regard, l'orientation de la tête, du buste et du corps, les gestes faciaux et brachio-manuels, etc – d'une grande complexité. La compréhension et la modélisation de ce type de communication est une étape cruciale dans le processus de la conception des agents interactifs capables d'engager des conversations crédibles avec des partenaires humains. Concrètement, un mod
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Chao, Tien, and 趙恬. "The Novel Decision Tree Classifier with Distance-based Concept Hierarchy Labels." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/17722686517337541811.

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碩士<br>輔仁大學<br>資訊管理學系<br>102<br>In recent years, data mining has become an efficient tool to analyze data, and is, still a hot issue in academia. In numerous data mining methods, decision tree has several advantages over other data mining methods and is popular in many business intelligent systems. Decision tree is mainly applied to prediction, and has a broad range of applications. Previous decision tree methods can only be applied to data with categorical labels, however, nowadays, the Big Data era is coming; more and more data were generated with different label types. For example, data labe
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Lei, Weng-U., and 李永裕. "A Decision Tree Classifier for Big Data Analytics on Credit Assessment Problem." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/39924892397011092983.

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碩士<br>國立臺灣大學<br>資訊管理學研究所<br>102<br>Credit assessment has been a large-scale problem among finance institutes. Their demand in reducing risk of customer debt can be achieved by applying data mining techniques to determine whether a new application should be approved or not. The problem, however, is actually under a Big Data environment. Complicated preprocessing steps are required because of the vast and messy data sources. The study proposes a Decision-Tree-Based Credit Assessment Approach (DTCAA) to solve the problem. Decision tree model is selected because of its interpretability and easily
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Hsu, Bo-Jr, and 許博智. "A Multi-Valued and Sequential Patterns Decision Tree Classifier for Data Mining." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/01654376819866143944.

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碩士<br>銘傳大學<br>資訊管理學系碩士班<br>98<br>Most of the decision tree classifiers require that attributes and temporal label of data set to be single-valued and non-sequential. However, there exist classification problems with multi-valued and sequential patterns data. Although some algorithms can handle the multi-valued and multi-labeled data, such as the MMC and MMDT, but they cannot handle sequential patterns label. Therefore, this research has developed a new decision tree classifier named MSDT (Multi-valued and Sequential Decision Tree). MSDT are different from the traditional decision tree classifi
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Yu, Wei-Yi, and 余威逸. "An Incremental-Learning Method for Supervised Anomaly Detection by Cascading Service Classifier and ITI Decision Tree Methods." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/58312906102245125209.

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碩士<br>國立臺灣科技大學<br>資訊工程系<br>97<br>Over the past years, an intrusion detection system (IDS) has been an essential part of computer system security. Especially data mining and analysis methodologies have been used to mining and learning data characteristics of attacks. Also, IDSs need to adaptive and accurate. For IDSs to be adaptive to different forms of data, these methodologies of IDSs have the capability of handling missing values, inconsistent instances. For IDSs to be accurate, how to use different kinds of methodologies to detect anomalies efficiently and accurately is still a main cha
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Chen, Hsiang-Chun, and 陳湘鈞. "Intelligent Signal Classifier for Brain Epileptic EEG Based on Decision Tree, Multilayer Perceptron and Over-Sampling Approach." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/72557141263228467311.

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碩士<br>國立中興大學<br>資訊管理學系所<br>104<br>Epilepsy is a chronic neurological disease induced by abnormal discharges of brain, it tends to experience recurrent unprovoked seizures. Seizures may lead to lose consciousness, uncontrollable muscle twitch and even possibly endanger one’s life. Electroencephalogram (EEG) is a common tool used in the clinical diagnosis and analysis of epilepsy. However, the visual examination of EEG is time-consuming, and also subjective that may affects the diagnostic results. Therefore, the aim of this study is to construct an automatic classifier for the epileptic EEG sign
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Melnychuk, Amie. "Multi-Temporal Crop Classification Using a Decision Tree in a Southern Ontario Agricultural Region." Thesis, 2012. http://hdl.handle.net/10214/4037.

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Identifying landuse management practices is important for detecting landuse change and impacts on the surrounding landscape. The Ontario Ministry of Agriculture and Rural A airs has established a database product called the Agricultural Resource Inventory (AgRI), which is used for the storage and analysis of agricultural land management practices. This thesis explores the opportunity to populate the AgRI. A comparison of two supervised classi fications using optical satellite imagery with multiple single-date classifi cations and a subsequent multi-date, multi-sensor classi fication were used
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Chen, Min-Hsien, and 陳民弦. "A Hybrid Classifier for Type 2 Diabetes Based on Decision Tree, Probabilistic Model and Artificial Neural Network- An Empirical Study of Taichung Tzu-chi General Hospital." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/83336301293216144685.

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碩士<br>國立中興大學<br>資訊管理學系所<br>105<br>The National Health Insurance of Taiwan has been gained 70% support from the peoples since 1995. The NHI costs is increasing year by year and keeps shortage of funds from 2007 to 2017, that seems NHI has high utilization rate. Taiwan&apos;&apos;s elderly population rate is increasing, and it will account for 20% of total population in 2025. With the increase of the elderly population, the burden of health care costs gets more and more .In 2016, annual top ten causes of death show that Diabetes was within the top 5 during 1995 to 2016. To achieve early prevent
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Hsu, Hsing-Yun, and 許馨勻. "A Hybrid Artificial Neural Network and Decision Tree Based Classifier to Vital Signs of Cardiopulmonary Resuscitation and Intensive Care Unit Patients in Taichung Tzu Chi Hospital." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/34222358377480042639.

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碩士<br>國立中興大學<br>資訊管理學系所<br>104<br>After admitted to the hospital, many patients need CPR or being transferred to ICU for observation with deteriorating conditions due to various reasons. The seven vital signs including body temperature, respiration, pulse, systolic blood pressure, diastolic blood pressure, degree of blood oxygen saturation and pain index are the most basic signals of the physical conditions and are the best indicating indexes that can reflect whether the body functions normally at the first moment. The visual checks are used as the main judgement basis in most of the hospitals
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Manwani, Naresh. "Supervised Learning of Piecewise Linear Models." Thesis, 2012. http://etd.iisc.ac.in/handle/2005/3244.

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Supervised learning of piecewise linear models is a well studied problem in machine learning community. The key idea in piecewise linear modeling is to properly partition the input space and learn a linear model for every partition. Decision trees and regression trees are classic examples of piecewise linear models for classification and regression problems. The existing approaches for learning decision/regression trees can be broadly classified in to two classes, namely, fixed structure approaches and greedy approaches. In the fixed structure approaches, tree structure is fixed before hand by
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39

Manwani, Naresh. "Supervised Learning of Piecewise Linear Models." Thesis, 2012. http://hdl.handle.net/2005/3244.

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Supervised learning of piecewise linear models is a well studied problem in machine learning community. The key idea in piecewise linear modeling is to properly partition the input space and learn a linear model for every partition. Decision trees and regression trees are classic examples of piecewise linear models for classification and regression problems. The existing approaches for learning decision/regression trees can be broadly classified in to two classes, namely, fixed structure approaches and greedy approaches. In the fixed structure approaches, tree structure is fixed before hand by
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Thanjavur, Bhaaskar Kiran Vishal. "Automatic generation of hardware Tree Classifiers." Thesis, 2017. https://hdl.handle.net/2144/23688.

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Machine Learning is growing in popularity and spreading across different fields for various applications. Due to this trend, machine learning algorithms use different hardware platforms and are being experimented to obtain high test accuracy and throughput. FPGAs are well-suited hardware platform for machine learning because of its re-programmability and lower power consumption. Programming using FPGAs for machine learning algorithms requires substantial engineering time and effort compared to software implementation. We propose a software assisted design flow to program FPGA for machine learn
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Hsu, Chang-Ling, and 許昌齡. "Multi-valued and Multi-labeled Decision Tree Classifiers for Data Mining." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/40316570391827175824.

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博士<br>國立中央大學<br>資訊管理研究所<br>92<br>Presently, decision tree classifiers require that attributes and class label of data set to be single-valued. However, there exist classification problems with multi-valued and multi-labeled data. Aiming to handle this multi-valued and multi-labeled data, this research has developed a decision tree classifier named MMC (Multi-valued and Multi-labeled Classifier) first. Then, by redesigning the algorithm, this research has further developed another classifier named MMDT (Multi-valued and Multi-labeled Decision Tree) to improve the accuracy of MMC. MMC and MMDT a
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Farid, D. M., L. Zhang, A. Hossain, et al. "An adaptive ensemble classifier for mining concept drifting data streams." 2013. http://hdl.handle.net/10454/9573.

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No<br>It is challenging to use traditional data mining techniques to deal with real-time data stream classifications. Existing mining classifiers need to be updated frequently to adapt to the changes in data streams. To address this issue, in this paper we propose an adaptive ensemble approach for classification and novel class detection in concept drifting data streams. The proposed approach uses traditional mining classifiers and updates the ensemble model automatically so that it represents the most recent concepts in data streams. For novel class detection we consider the idea that data po
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CHI, HSING-CHEN, and 紀幸辰. "A Machine Learning Based Prediction System of Medical Laws Judgment Using Statute-Classified Decision Tree with Text Similarity." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/gxyh35.

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碩士<br>國立臺北大學<br>資訊工程學系<br>107<br>The retrieval of legal documents takes a considerable time, in which predictive accuracy of the file is an important issue in the law domain. The legal documents (judgments) record the legal reasons, processes and applicable statutes of the law. Because the verdict did not clearly indicate the outcome of the lawsuit. The result need to analyze the law and corpus through the comparison between the judgments. In this thesis, we propose the prediction system of medical laws based on machine learning. The system predicts the result of lawsuit through the statute an
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(9136835), Sungbum Jun. "SCHEDULING AND CONTROL WITH MACHINE LEARNING IN MANUFACTURING SYSTEMS." Thesis, 2020.

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Numerous optimization problems in production systems can be considered as decision-making processes that determine the best allocation of resources to tasks over time to optimize one or more objectives in concert with big data. Among the optimization problems, production scheduling and routing of robots for material handling are becoming more important due to their impacts on system performance. However, the development of efficient algorithms for scheduling or routing faces several challenges. While the scheduling and vehicle routing problems can be solved by mathematical models such as mixed
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Costa, Hugo Alexandre Gomes da. "Estratégia multi-temporal para produção automática de cartografia de ocupação do solo com imagens AWiFS." Master's thesis, 2009. http://hdl.handle.net/10362/2347.

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Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica<br>A produção de cartografia de ocupação do solo por métodos tradicionais (interpretação visual de imagens aéreas e de satélite) é um processo com custos que inviabilizam a sua rápida produção e frequente actualização. Esta realidade é bastante lesante para diversas aplicações que necessitam deste género de informação actualizada. Uma solução viável para fazer face à problemática da desactualização da cartografia de ocupação do solo é a criação de um produto menos
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(12214559), Sonal Chawda. "Determination of distance relay characteristics using an inductive learning system." Thesis, 1993. https://figshare.com/articles/thesis/Determination_of_distance_relay_characteristics_using_an_inductive_learning_system/19326599.

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<div>In this research an attempt has been made to design distance relays as per protection system requirements. This is achieved by using an Inductive learning technique. The inductive learning algorithm which belongs to the family of machine learning by examples is used to convert a set of impedance values into a decision tree. The impedance values are obtained by conducting fault study on the system to be protected. A number of tests have been carried out on various transmission line configurations. The required software for generating the</div><div>decision tree has been developed.</div>
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Paiva, Bárbara Cecília Bessa dos Santos Oliveiros. "Técnicas de Classificação, Diagnóstico e Avaliação de Risco em Doenças com Compromisso da Visão." Doctoral thesis, 2015. http://hdl.handle.net/10316/26583.

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Tese de doutoramento em Ciências da Saúde, no ramo de Ciências Biomédicas, apresentada à Faculdade de Medicina da Universidade de Coimbra<br>As doenças da visão incluem a cegueira e a baixa visão, e afetam cerca de 4,25% da população mundial. Cerca de 80% destas podem ser prevenidas ou curadas. Estas estimativas, da Organização Mundial de Saúde, referem que 82% das pessoas com cegueira têm 50 ou mais anos. A sua prevalência está relacionada com o envelhecimento da população, emergindo neste contexto as doenças do segmento posterior. Nestas, inclui-se a retinopatia diabética, uma manifestação c
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