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Dissertations / Theses on the topic 'Decision Tree Algorithm'

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Published: 4 June 2021
Last updated: 25 July 2025

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1

Shi, Haijian. "Best-first Decision Tree Learning." The University of Waikato, 2007. http://hdl.handle.net/10289/2317.

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In best-first top-down induction of decision trees, the best split is added in each step (e.g. the split that maximally reduces the Gini index). This is in contrast to the standard depth-first traversal of a tree. The resulting tree will be the same, just how it is built is different. The objective of this project is to investigate whether it is possible to determine an appropriate tree size on practical datasets by combining best-first decision tree growth with cross-validation-based selection of the number of expansions that are performed. Pre-pruning, post-pruning, CART-pruning can be perfo
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2

Kassim, M. E. "Elliptical cost-sensitive decision tree algorithm (ECSDT)." Thesis, University of Salford, 2018. http://usir.salford.ac.uk/47191/.

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Cost-sensitive multiclass classification problems, in which the task of assessing the impact of the costs associated with different misclassification errors, continues to be one of the major challenging areas for data mining and machine learning. The literature reviews in this area show that most of the cost-sensitive algorithms that have been developed during the last decade were developed to solve binary classification problems where an example from the dataset will be classified into only one of two available classes. Much of the research on cost-sensitive learning has focused on inducing d
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Girardini, Davide <1985&gt. "Efficient implementation of Treant: a robust decision tree learning algorithm." Master's Degree Thesis, Università Ca' Foscari Venezia, 2020. http://hdl.handle.net/10579/17423.

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The thesis focuses on the optimization of an existing algorithm called Treant for the generation of robust decision trees. Despite its good performances from the machine learning point of view, unfortunately, the code presented some strong limitations when employed with big datasets. The algorithm was originally written in Python, a very good programming language for fast prototyping but, as well as many other interpreted languages, it can lead to poor performances when it is asked to crunch a big amount of numbers if not supported by appropriated libraries. The code has been translated to the
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4

Trivedi, Ankit P. "Decision tree-based machine learning algorithm for in-node vehicle classification." Thesis, California State University, Long Beach, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10196455.

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<p> This paper proposes an in-node microprocessor-based vehicle classification approach to analyze and determine the types of vehicles passing over a 3-axis magnetometer sensor. The approach for vehicle classification utilizes J48 classification algorithm implemented in Weka (a machine learning software suite). J48 is Quinlan's C4.5 algorithm, an extension of decision tree machine learning based on an ID3 algorithm. The decision tree model is generated from a set of features extracted from vehicles passing over the 3-axis sensor. The features are attributes provided with correct classification
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Hari, Vijaya. "Empirical Investigation of CART and Decision Tree Extraction from Neural Networks." Ohio University / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1235676338.

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Krook, Jonatan. "Predicting low airfares with time series features and a decision tree algorithm." Thesis, Uppsala universitet, Statistiska institutionen, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-353274.

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Airlines try to maximize revenue by letting prices of tickets vary over time. This fluctuation contains patterns that can be exploited to predict price lows. In this study, we create an algorithm that daily decides whether to buy a certain ticket or wait for the price to go down. For creation and evaluation, we have used data from searches made online for flights on the route Stockholm – New York during 2017 and 2018. The algorithm is based on time series features selected by a decision tree and clearly outperforms the selected benchmarks.
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Feychting, Sara. "Incredible tweets : Automated credibility analysis in Twitter feeds using an alternating decision tree algorithm." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-186711.

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This project investigates how to determine the credibility of a tweet without using human perception. Information about the user and the tweet is studied in search for correlations between their properties and the credibility of the tweet. An alternating decision tree is created to automatically determine the credibility of tweets. Some features are found to correlate to the credibility of the tweets, amongst which the number of previous tweets by a user and the use of uppercase characters are the most prominent.
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8

Gerdes, Mike. "Predictive Health Monitoring for Aircraft Systems using Decision Trees." Licentiate thesis, Linköpings universitet, Fluida och mekatroniska system, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-105843.

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Unscheduled aircraft maintenance causes a lot problems and costs for aircraft operators. This is due to the fact that aircraft cause significant costs if flights have to be delayed or canceled and because spares are not always available at any place and sometimes have to be shipped across the world. Reducing the number of unscheduled maintenance is thus a great costs factor for aircraft operators. This thesis describes three methods for aircraft health monitoring and prediction; one method for system monitoring, one method for forecasting of time series and one method that combines the two oth
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Doubleday, Kevin. "Generation of Individualized Treatment Decision Tree Algorithm with Application to Randomized Control Trials and Electronic Medical Record Data." Thesis, The University of Arizona, 2016. http://hdl.handle.net/10150/613559.

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With new treatments and novel technology available, personalized medicine has become a key topic in the new era of healthcare. Traditional statistical methods for personalized medicine and subgroup identification primarily focus on single treatment or two arm randomized control trials (RCTs). With restricted inclusion and exclusion criteria, data from RCTs may not reflect real world treatment effectiveness. However, electronic medical records (EMR) offers an alternative venue. In this paper, we propose a general framework to identify individualized treatment rule (ITR), which connects the subg
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McNamara, Nathan Patrick. "Using Decision Trees to Predict Intent to Use Passive Occupational Exoskeletons in Manufacturing Tasks." Ohio University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1605720844135027.

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11

Johansson, Viktor. "A sensor orientation and signal preprocessing study of a personal fall detection algorithm." Thesis, Högskolan Kristianstad, Fakulteten för naturvetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hkr:diva-21375.

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This study investigates if a smartphones orientation in the pocket affects the result of a decision tree model trained with data from personal falls, and also how a low-pass filter affects these results. A comparison is made between the results gathered from this study, compared to previous studies and products within the field. The data was gathered using a smartphone application and was later split up to get datasets for all the different orientations of the smartphone. Before training the models, the data was processed through a low pass filter. Results showed that low pass filtered signals
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Rodríguez, Elen Yanina Aguirre. "Técnicas de aprendizado de máquina para predição do custo da logística de transporte : uma aplicação em empresa do segmento de autopeças /." Guaratinguetá, 2020. http://hdl.handle.net/11449/192326.

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Orientador: Fernando Augusto Silva Marins<br>Resumo: Em diferentes aspectos da vida cotidiana, o ser humano é forçado a escolher entre várias opções, esse processo é conhecido como tomada de decisão. No nível do negócio, a tomada de decisões desempenha um papel muito importante, porque dessas decisões depende o sucesso ou o fracasso das organizações. No entanto, em muitos casos, tomar decisões erradas pode gerar grandes custos. Desta forma, alguns dos problemas de tomada de decisão que um gerente enfrenta comumente são, por exemplo, a decisão para determinar um preço, a decisão de comprar ou f
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Astapenko, D. "Automated system design optimisation." Thesis, Loughborough University, 2010. https://dspace.lboro.ac.uk/2134/6863.

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The focus of this thesis is to develop a generic approach for solving reliability design optimisation problems which could be applicable to a diverse range of real engineering systems. The basic problem in optimal reliability design of a system is to explore the means of improving the system reliability within the bounds of available resources. Improving the reliability reduces the likelihood of system failure. The consequences of system failure can vary from minor inconvenience and cost to significant economic loss and personal injury. However any improvements made to the system are subject t
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Khan, Kashif. "A distributed computing architecture to enable advances in field operations and management of distributed infrastructure." Thesis, University of Manchester, 2012. https://www.research.manchester.ac.uk/portal/en/theses/a-distributed-computing-architecture-to-enable-advances-in-field-operations-and-management-of-distributed-infrastructure(a9181e99-adf3-47cb-93e1-89d267219e50).html.

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Distributed infrastructures (e.g., water networks and electric Grids) are difficult to manage due to their scale, lack of accessibility, complexity, ageing and uncertainties in knowledge of their structure. In addition they are subject to loads that can be highly variable and unpredictable and to accidental events such as component failure, leakage and malicious tampering. To support in-field operations and central management of these infrastructures, the availability of consistent and up-to-date knowledge about the current state of the network and how it would respond to planned interventions
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15

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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Odeh, Khaled. "Nouveaux algorithmes pour le traitement probabiliste et logique des arbres de défaillance." Compiègne, 1995. http://www.theses.fr/1995COMPD846.

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L'arbre de défaillance est un outil majeur dans les études de sûreté de fonctionnement des systèmes complexes. Ce modèle représente graphiquement les combinaisons d'événements conduisant à la réalisation de l'événement indésirable. Les analyses qualitative et quantitative de ce modèle sont des problèmes NP-difficiles. Notre but est de développer de nouveaux algorithmes et d'améliorer les algorithmes existants pour que l'on puisse effectuer ces analyses sur des gros arbres de défaillance. Nous proposons un algorithme de factorisation par rapport aux événements répétés et complémentaires afin de
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17

Cazzolato, Mirela Teixeira. "Classificação de data streams utilizando árvore de decisão estatística e a teoria dos fractais na análise evolutiva dos dados." Universidade Federal de São Carlos, 2014. https://repositorio.ufscar.br/handle/ufscar/565.

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Made available in DSpace on 2016-06-02T19:06:13Z (GMT). No. of bitstreams: 1 5984.pdf: 1962060 bytes, checksum: d943b973e9dd5f12ab87985f7388cb80 (MD5) Previous issue date: 2014-03-24<br>Financiadora de Estudos e Projetos<br>A data stream is generated in a fast way, continuously, ordered, and in large quantities. To process data streams there must be considered, among others factors, the limited use of memory, the need of real-time processing, the accuracy of the results and the concept drift (which occurs when there is a change in the concept of the data being analyzed). Decision tree is a p
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Barros, Rodrigo Coelho. "On the automatic design of decision-tree induction algorithms." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-21032014-144814/.

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Decision-tree induction is one of the most employed methods to extract knowledge from data. There are several distinct strategies for inducing decision trees from data, each one presenting advantages and disadvantages according to its corresponding inductive bias. These strategies have been continuously improved by researchers over the last 40 years. This thesis, following recent breakthroughs in the automatic design of machine learning algorithms, proposes to automatically generate decision-tree induction algorithms. Our proposed approach, namely HEAD-DT, is based on the evolutionary algorith
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Tsang, Pui-kwan Smith, and 曾沛坤. "Efficient decision tree building algorithms for uncertain data." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2008. http://hub.hku.hk/bib/B41290719.

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Tsang, Pui-kwan Smith. "Efficient decision tree building algorithms for uncertain data." Click to view the E-thesis via HKUTO, 2008. http://sunzi.lib.hku.hk/hkuto/record/B41290719.

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Cagnini, Henry Emanuel Leal. "Estimation of distribution algorithms for clustering and classification." Pontif?cia Universidade Cat?lica do Rio Grande do Sul, 2017. http://tede2.pucrs.br/tede2/handle/tede/7384.

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Submitted by Caroline Xavier (caroline.xavier@pucrs.br) on 2017-06-29T11:51:00Z No. of bitstreams: 1 DIS_HENRY_EMANUEL_LEAL_CAGNINI_COMPLETO.pdf: 3650909 bytes, checksum: 55d52061a10460875dba677a9812fe9c (MD5)<br>Made available in DSpace on 2017-06-29T11:51:00Z (GMT). No. of bitstreams: 1 DIS_HENRY_EMANUEL_LEAL_CAGNINI_COMPLETO.pdf: 3650909 bytes, checksum: 55d52061a10460875dba677a9812fe9c (MD5) Previous issue date: 2017-03-20<br>Extrair informa??es relevantes a partir de dados n?o ? uma tarefa f?cil. Tais dados podem vir a partir de lotes ou em fluxos cont?nuos, podem ser completos ou poss
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Pazúriková, Jana. "Adaptivní model pro simulaci znečištění ovzduší." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2012. http://www.nusl.cz/ntk/nusl-236487.

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Air pollution harms the environment and human welfare. Computer models and their simulation are useful tools for deeper understanding of processes behind as they quite accurately represent the dispersion and transformation of pollutants with advection diffusion equation or by other concepts. Current models give valid results only to constrained cases of initial conditions. The general model combining the several specific models which is able to change according to input parametres and improve with training is proposed. The adaptiveness of the system is provided by decision tree as data structu
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Yu, Peng. "Improving Decision Tree Learning." Electronic Thesis or Diss., Institut polytechnique de Paris, 2024. http://www.theses.fr/2024IPPAT037.

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La modélisation par arbres de décision est reconnue pour son efficacité et sa lisibilité, notamment pour les données structurées. Cette thèse s’attaque à deux défis majeurs : l’interprétabilité des arbres profonds et la gestion des variables catégorielles.Nous présentons l’algorithme Linear Tree- Shap, qui facilite l’explication du processus décisionnel en attribuant des scores d’importance à chaque noeud et variable. Parallèlement, nous proposons un cadre méthodologique pour traiter directement les variables catégorielles, améliorant à la fois la précision et la robustesse du modèle. Notre ap
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DIRUTIGLIANO, DOMENICO. "The role of the energy performance modelling with a view to low energy buildings." Doctoral thesis, Politecnico di Torino, 2018. http://hdl.handle.net/11583/2711481.

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Climate change requires courageous choices, the European Union has accepted this challenge. One of the 2050 European low-carbon targets is energy savings in the building sector which is responsible for around 40% of energy consumption and 36% of CO2 emissions in the EU. The role of Building Performance Simulation (BPS) is central in that it allows to improve the design, optimization, construction, operation and maintenance of new and existing buildings. In order to achieve the correct estimate of energy consumption of buildings, different models have been developed in the last decades. They c
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Basgalupp, Márcio Porto. "LEGAL-Tree: um algoritmo genético multi-objetivo para indução de árvores de decisão." Universidade de São Paulo, 2010. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-12052010-165344/.

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Dentre as diversas tarefas em que os algoritmos evolutivos têm sido empregados, a indução de regras e de árvores de decisão tem se mostrado uma abordagem bastante atrativa em diversos domínios de aplicação. Algoritmos de indução de árvores de decisão representam uma das técnicas mais populares em problemas de classificação. Entretanto, os algoritmos tradicionais de indução apresentam algumas limitações, pois, geralmente, usam uma estratégia gulosa, top down e com particionamento recursivo para a construção das árvores. Esses fatores degradam a qualidade dos dados, os quais podem gerar regras e
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Sjunnebo, Joakim. "Application of the Boosted Decision Tree Algorithmto Waveform Discrimination." Thesis, KTH, Fysik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-129408.

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The Polarised Gamma-ray Observer (PoGOLite) is a balloon-borne experiment aimed at measuring the polarisation of hard X-rays from astronomical sources. In the planned flight environment the neutron background is high. A smaller version of PoGOLite, named PoGOLino, was constructed with the goal of measuring the neutron background rates and was launched in March 2013. The signals produced in the detectors of both these instruments give rise to waveforms of different shapes depending on the type of detector the interaction occurred in. A method to distinguish between signal and background wavefor
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Rangwala, Maimuna H. "Empirical investigation of decision tree extraction from neural networks." Ohio : Ohio University, 2006. http://www.ohiolink.edu/etd/view.cgi?ohiou1151608193.

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Frizzarini, Cláudio. "Algoritmo para indução de árvores de classificação para dados desbalanceados." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/100/100131/tde-19022014-101043/.

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As técnicas de mineração de dados, e mais especificamente de aprendizado de máquina, têm se popularizado enormemente nos últimos anos, passando a incorporar os Sistemas de Informação para Apoio à Decisão, Previsão de Eventos e Análise de Dados. Por exemplo, sistemas de apoio à decisão na área médica e ambientes de \\textit{Business Intelligence} fazem uso intensivo dessas técnicas. Algoritmos indutores de árvores de classificação, particularmente os algoritmos TDIDT (Top-Down Induction of Decision Trees), figuram entre as técnicas mais comuns de aprendizado supervisionado. Uma das vantagens d
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Baker, Peter John. "Applied Bayesian modelling in genetics." Thesis, Queensland University of Technology, 2001.

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Konda, Ramesh. "Predicting Machining Rate in Non-Traditional Machining using Decision Tree Inductive Learning." NSUWorks, 2010. http://nsuworks.nova.edu/gscis_etd/199.

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Wire Electrical Discharge Machining (WEDM) is a nontraditional machining process used for machining intricate shapes in high strength and temperature resistive (HSTR) materials. WEDM provides high accuracy, repeatability, and a better surface finish; however the tradeoff is a very slow machining rate. Due to the slow machining rate in WEDM, machining tasks take many hours depending on the complexity of the job. Because of this, users of WEDM try to predict machining rate beforehand so that input parameter values can be pre-programmed to achieve automated machining. However, partial success wit
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Crockett, Keeley Alexandria. "Fuzzy rule induction from data domains." Thesis, Manchester Metropolitan University, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.243720.

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Chiu, Chun-Chieh, and 邱俊傑. "CUDT: A CUDA Based Decision Tree Algorithm." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/88189185018035112843.

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碩士<br>國立交通大學<br>資訊科學與工程研究所<br>99<br>Classification is an important issue both in Machine Learning and Data Mining. Decision tree is one of the famous classification models. In the reality case, the dimension of data is high and the data size is huge. Building a decision in large data base cost much time in computation. It is a computationally expensive problem. GPU is a special design processor of graphic. The highly parallel features of graphic processing made today’s GPU architecture. GPGPU means use GPU to solve non-graphic problems which need amounts of computation power. Since the high p
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Lai, Jian-Cheng, and 賴建丞. "Fast Quad-Tree Depth Decision Algorithm for HEVC Coding Tree Block." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/39ucm4.

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碩士<br>國立虎尾科技大學<br>資訊工程研究所<br>102<br>High Efficiency Video Coding (HEVC) is recently developed for ultra high definition video compression technique, which provides a higher compression ratio and throughput compared with previously video compression standard H.264/AVC. Therefore, this technique is widely used to limited bandwidth network transmission and confined storage space. In order to obtain the higher compression ratio and maintain video quality, which provides variable block partition and mode prediction for HEVC encoder. If each block is computed during the mode decision process, a lot
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Hsieh, Cheng-Hao, and 謝正豪. "An Approach with Bat Algorithm and Decision Tree." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/38211713696274285313.

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碩士<br>華梵大學<br>資訊管理學系碩士班<br>102<br>The amount of information is rapidly increasing. Data mining is widely used. Decision tree can process data and provide the rules of tree structure, so that decision-maker can rapidly obtain information behind the hidden data. Therefore, decision tree can be used to solve problems from other domains. It should set the parameters before using decision tree, because how to properly set the parameters will affect the results. It is an important issue to adjust the parameters of decision tree. The different problems have different best parameters of decision tree.
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Tsai, Yu-Ju, and 蔡育儒. "Paralleled CHAID Decision Tree Algorithm with Big-Data Capability." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/08393327566226485549.

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碩士<br>淡江大學<br>統計學系碩士班<br>102<br>As technology advances, the era of Big-Data has finally arrived. As the amount of data increases , the improvement of computing speed becomes an important development technology. If data training and analysis time are reduced, we could make the prediction or decision much earlier then expected. As a result, parallel computation is one of the methods which can reduce the analysis time. In this paper, we rewrite the CHAID decision tree algorithm for parallel computation and Big-Data capability. Our simulation results show that, when the CPU has more than one kern
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Lanning, James Michael. "A kernelized genetic algorithm decision tree with information criteria." 2008. http://etd.utk.edu/2008/August2008Dissertations/LanningJamesMichael.pdf.

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Shiau, Fang-Jr, and 蕭方智. "Developing a Hierarchical Particle Swarm based Fuzzy Decision Tree Algorithm." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/38520035342800327252.

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碩士<br>元智大學<br>工業工程與管理學系<br>93<br>Decision tree is one of most common techniques for classification problems in data mining. Recently, fuzzy set theory has been applied to decision tree construction to improve its performance. However, how to design flexile fuzzy membership functions for each attribute and how to reduce the total number of rules and improve the classification interpretability are two major concerns. To solve the problems, this research proposes a hieratical particle swarm optimization to develop a fuzzy decision tree algorithm (HPS-FDT). In this proposed HPS-FDT algorithm, all
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Chang, Tien-Wei, and 張添瑋. "Using Expert Decision Tree Algorithm in Computer Assisted Testing System." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/5qd4ng.

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碩士<br>國立嘉義大學<br>資訊工程學系研究所<br>97<br>Since different person has different learning method that suits him/her, the adaptive learning is hard to be reached through the existed single feedback assessment mechanism. This thesis integrated a set of expert decision tree algorithm to build up the regularity between learning type and teaching strategy. The regularity is embedded into the computer assisted system to set up new diversified teaching assessment system. Experts’ teaching experiments and KLSI Inventory are used to set up the rules of learning type knowledge database in the system. Based on th
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Guo, Jin-Jhong, and 郭金忠. "Medical and Biological Datasets Using Decision Tree and Genetic Algorithm." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/16671173991554268590.

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碩士<br>國立雲林科技大學<br>工業工程與管理研究所碩士班<br>94<br>This study describes the application of decision tree and genetic algorithm (GA) to evolve useful subset of discriminatory features for medical and biological data. We have shown that a GA combined with decision tree performs well in extracting information about the relationship between biological variables. The result suggests that six feature set evolutions : Aspartate aminotransferase (GOT)、HBV Surface Ag (HBs-Ag)、Blood urea nitrogen (BUN)、Globulin (Glo)、White blood cell count(WBC)、Electrolyte Ca(Ca) are appropriate for our large dataset. Those f
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Lin, Yi-Kun, and 林義坤. "Apply Decision Tree Algorithm to the Analysis of Web Log." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/17894208644016211291.

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碩士<br>華梵大學<br>資訊管理學系碩士班<br>99<br>With the rapid development of Internet and network services increased, the network has imperceptibly become an important tool in our lives, which makes network security events be endless. In these events, the reasons of many attacked websites by hackers are most of web application programmers who have no awareness of network security. Then, vulnerabilities are existed in websites such as Cross Site Request Forgeries (CSRF), SQL Injection, Script Insertion, and Cross Site Scripting (XSS). The attacked websites would lead to serious damages of data leakage for pe
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Yu, Li, and 游力. "Dynamic Ensemble Decision Tree Learning Algorithm for Network Traffic Classification." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/cyqff7.

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碩士<br>國立交通大學<br>網路工程研究所<br>104<br>Network traffic classification has already been discussed for decades, which gives us the ability to monitor and detect the applications associated with network traffic. It becomes the essential step of network management and traffic engineering such as QoS control, abnormal detection and ISPs network planing. From the earliest approach, which is the port base classification, to the state of the art practice, which is the machine learning classification. Beside, most of the information technology research and advisory organizations have forecast that we are go
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LIN, SU CHING, and 蘇清霖. "Building a salary predictive analysis model using the decision tree algorithm." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/23503546290538682457.

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碩士<br>僑光科技大學<br>資訊科技研究所<br>101<br>With evolution of technology and vigorous development of Internet, people no longer just simply record information. Instead, they analyze such data to discover its potential usage for certain knowledge, or analyze the existing facts to produce result forecasting further information, which then contribute for society usage. In recent years, the emergence of the domestic job recruiter website utilizes the advantages of the Internet for job seekers, and provides convenience, interactive and richness of information, which constitutes a sharp contrast to the trad
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Wang, Yuang-Jang, and 王元璋. "A fuzzy decision tree with fuzzy entropy turned by genetic algorithm." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/25559225344644267556.

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碩士<br>國立成功大學<br>資訊管理研究所<br>94<br>The decision tree is one of data mining methodologies. It generates rules via learning to provide back-end information to decision support systems (DSS) or executive information system (EIS) for decision making. Regular decision trees lack of ability to deal with uncertainty. Fuzzy decision trees handle uncertainty using linguistic variable with adjustable membership functions. The membership function of fuzzy decision tree can adapt itself to various situation for gaining decision accuracy. 　　This study builds two kinds of classification model. The first type
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Chen, Ming-Shiang, and 陳明祥. "Predicting Student Deviation Behavior By Hybrid Genetic Algorithm/Decision Tree Approach." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/75138559893452241385.

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碩士<br>華梵大學<br>資訊管理學系碩士班<br>94<br>Abstract Because of the changes of the times, the multiple-society, the pressure of school, family, and individual factor, etc., many students' deviant behaviors take place more often. Once students' deviant behaviors happen, it may be difficult to compensate the great impact on individual or group. This research by utilizing superior information technology that uses a hybrid Genetic algorithm (GA) & Decision trees (DT) approach, to predict if the student has a tendency toward deviance. The experimental results demonstrated：in 116 attributes, gender, whether th
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LAI, I.-CHIEN, and 賴以建. "GENETIC ALGORITHM, NEURAL NETWORK AND DECISION TREE IN PRE-WARNING MODELS." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/34939994824622402263.

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碩士<br>國立臺北大學<br>企業管理學系<br>91<br>In the past, the pre-warning models for Financial Crisis are usually established based on traditional statistical methods such as Discriminant Analysis. However, it is often questionable whether the financial data satisfies the assumptions of such models. Therefore, this study investigates the construction of pre-warning model through nonlinear methods such as Genetic Algorithm and Neural Network. In additional, since the reference value for the key indicator that influences business failure most cannot be extracted from the pre-warning model, this study starts
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Šurín, Lukáš. "Využitie genetických algoritmov pri tvorbe rozhodovacích stromov." Master's thesis, 2015. http://www.nusl.cz/ntk/nusl-350916.

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Decision trees are recognized and widely used technique for processing and analyzing data. These trees are designed with typical and generally known inductive techniques (such as ID3, C4.5, C5.0, CART, CHAID, MARS). Predictive power of created trees is not always perfect and they often provide a room for improvement. Induction of trees with difficult criterias is hard and sometime impossible. In this paper we will deal with decision trees, namely their creation. We use the mentioned room for improvement by metaheuristic, genetic algorithms, which is used in all types of optimalization. The wor
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Sheif, Kuo-yeith, and 謝國義. "An improved algorithm to reduce the computational complexity in decision tree generation." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/33259286892116275891.

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Fann, Wen-Chih, and 范文誌. "Predicting mortality in patients with necrotizing fasciitis by using decision tree algorithm." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/51141977925238132643.

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碩士<br>臺北醫學大學<br>醫學資訊研究所<br>97<br>Objective: To identify simple admission clinical characteristics or laboratory tests to predict mortality but also differentiate between high and low mortality risk groups in patients with necrotizing fasciitis. Methods: This retrospective chart-review study included adult patients who were admitted to two hospitals through the emergency department with the discharge diagnosis of necrotizing fasciitis. Both the chi-square test (or the Mann-Whitney-U test) and C4.5 decision tree were utilized to analyze 23 variables among clinical characteristics and laboratory
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TSOU, YU-CHIEH, and 鄒侑捷. "Application of Decision Tree Algorithm to Item Selection Strategies in Multistage Testing." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/e97vsd.

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碩士<br>輔仁大學<br>統計資訊學系應用統計碩士班<br>107<br>The purpose of this study is to combination decision tree model and test theory and applies to the multi-stage test. The result indicate that the classification correct rate and rooted mean square error of decision tree selection, Fisher information and KL information method are better than random selection. Under the one-parameter model hypothesis, the cost of decision tree method, FI information method and KL information method is similar when the student’s ability is under uniform distribution hypothesis. However, when the student’s ability is under nor
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Hsu, Yung-Cheng, and 許永錚. "Using Decision Tree Algorithm for the Detection and Decision Rule Construction of Defect on Dispensing Process." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/t4k2s7.

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碩士<br>國立中山大學<br>資訊管理學系研究所<br>106<br>In recent years, due to the advancement of information technology, the analysis and research of big data has been widely applied in various industrial fields. The new thinking that brings different industries to various industries lies in the application of industrial innovation. Surface Mount Technology (SMT) - Dispensing Processes often used in IC packaging and testing, can easily lead to the occurrence of defective products due to many accidental factors, defects are then discovered through product inspection and testing after the dispensing process.
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