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Relevant bibliographies by topics / Piecewise linear regression / Dissertations / Theses

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Dissertations / Theses on the topic 'Piecewise linear regression'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Gormley, Nolan D. "Knotilus: A Differentiable Piecewise Linear Regression Framework." Bowling Green State University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1617222994436272.

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2

FASOLA, Salvatore. "Change-point estimation in piecewise constant regression models and extensions." Doctoral thesis, Università degli Studi di Palermo, 2015. http://hdl.handle.net/10447/105107.

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3

Pettersson, Angelica. "Något om regressionsanalys." Thesis, Örebro University, School of Science and Technology, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-10705.

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<p>En gren inom statistikteorin är den så kallade Regressionsanalysen där man studerar hur data från exempelvis ett stickprov kan anpassas till en graf. Skrivandet av denna uppsats har haft som syfte att studera några av de metoder som finns att tillgå vid bestämning av de ingående parametrarna i de enklare fallen av regression. Dessutom ges i de avslutande kapitlen exempel på den del inom regressionsanalysen som kallas Styckvis Linjär Regression eller <em>Piecewise Linear Regression.</em></p><br>Presentationen är redan avklarad den 26 april 2010 kl. 11.30

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4

Van, der Westhuizen Magdelena Marianna. "Robust techniques for regression models with minimal assumptions / M.M. van der Westhuizen." Thesis, North-West University, 2011. http://hdl.handle.net/10394/6689.

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Good quality management decisions often rely on the evaluation and interpretation of data. One of the most popular ways to investigate possible relationships in a given data set is to follow a process of fitting models to the data. Regression models are often employed to assist with decision making. In addition to decision making, regression models can also be used for the optimization and prediction of data. The success of a regression model, however, relies heavily on assumptions made by the model builder. In addition, the model may also be influenced by the presence of outliers; a more robu

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5

Ohlsson, Henrik, and Lennart Ljung. "Identification of switched linear regression models using sum-of-norms regularization." Linköpings universitet, Reglerteknik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-92612.

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This paper proposes a general convex framework for the identification of switched linear systems. The proposed framework uses over-parameterization to avoid solving the otherwise combinatorially forbidding identification problem, and takes the form of a least-squares problem with a sum-of-norms regularization, a generalization of the ℓ1-regularization. The regularization constant regulates the complexity and is used to trade off the fit and the number of submodels.<br><p>Funding Agencies|Swedish foundation for strategic research in the center MOVIII||Swedish Research Council in the Linnaeus ce

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6

Sousa, F. Raquel R. F. de. "Exploratory spatial analysis of topographic surface metrics for the prediction of water table occurrence." Master's thesis, Universidade de Évora, 2014. http://hdl.handle.net/10174/12215.

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Starting from the premise that water table in aquifers follows topographic surface as well as underground flow direction tends to be consistent with the surface streams flow directions, the present work presents the essays of the research to define a model that predicts, through a piecewise multiple regression, groundwater level in the Estremoz-Cano Aquifer System and in the surrounding igneous and metamorphic rocks of the OMZ as a function of topography, namely a set of terrain metrics like curvature and structural curvature to be related with the static water level (SWL) measured on dug well

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7

Huang, Min Ching. "Piecewise linear tree-structured regression." 1989. http://catalog.hathitrust.org/api/volumes/oclc/21951798.html.

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Thesis (Ph. D.)--University of Wisconsin--Madison, 1989.<br>Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 101-104).

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8

Kademan, Edmund John. "Piecewise linear regression through random partitioning." 1993. http://catalog.hathitrust.org/api/volumes/oclc/31038585.html.

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Thesis (Ph. D.)--University of Wisconsin--Madison, 1993.<br>Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 68-69).

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9

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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10

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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11

Borgesi, Jennifer Jo. "A piecewise linear generalized poisson regression approach to modeling longitudinal frequency data." 2004. http://etd1.library.duq.edu/theses/available/etd-04162004-162908/.

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12

Yi-Hsi, Huang. "Sample-Efficient Regression Trees for Attributes with Mixed Continuous and Discrete Effects-A Piecewise-Linear Regression Tree." 2005. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0001-1507200516252800.

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13

Huang, Yi-Hsi, and 黃奕禧. "Sample-Efficient Regression Trees for Attributes with Mixed Continuous and Discrete Effects-A Piecewise-Linear Regression Tree." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/96903937219531216195.

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碩士<br>國立臺灣大學<br>工業工程學研究所<br>93<br>Classification and regression trees (CART) is a type of decision-tree techniques, used to deal with either categorical or continuous response. A shortcoming of the regression tree is that the splitting procedure exhausts the sample size quickly. Sample-Efficient Regression Trees (SERT) is developed to address the sample-size-depleting issue. However, both SERT and CART are only able to select the attributes with discrete effects. The attributes with continuous effects, variant continuous effects, and mixed effects will not be selected into the tree model by CA

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14

Fu, Huang Tai, and 黃泰孚. "Constructing Takagi-Sugeno Fuzzy System Model by Slip Window and Piecewise Linear Regression Analysis Structure." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/17276973931235010378.

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碩士<br>國立臺灣科技大學<br>電機工程系<br>88<br>The approaches of modeling complex non-linear systems can basically be classified into global and local methods. The global method uses the non-linear relationship existing among system variables to model the system. Whereas, the local method separates a whole system into several linear sub-system that are smaller in size and easier in implementation to avoid dealing directly with complex and non-linear properties of the system. The concept of local method is close to the way of solving problem being has done. The Takagi—Sugeno model ( TS model ), ex

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15

Ngai, Kwok-Wang, and 倪國宏. "Cycle-Time-Aware Semiconductor Manufacturing Yield Analysis using Stepwise Regression with Pearson Correlation Approximation and Piecewise Linear Modeling." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/96956859657858132474.

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碩士<br>元智大學<br>工業工程與管理學系<br>99<br>In semiconductor manufacturing, yield loss is not only due to impropriate settings of individual process recipes but also associated with longer cycle time. On the one hand, wafer lot in some specific process steps with longer cycle time is more likely to be contaminated by particles or oxidized. On the other hand, an abnormal event sometime may result in low yield with longer cycle time. Therefore, cycle time has become either a direct or indirect factor to yield loss. Using cycle time data for yield analysis is a new topic in semiconductor manufacturing. Ther

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16

Huang, Yunkai. "Non-global regression modelling." Thesis, 2016. http://hdl.handle.net/1828/7346.

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In this dissertation, a new non-global regression model - the partial linear threshold regression model (PLTRM) - is proposed. Various issues related to the PLTRM are discussed. In the first main section of the dissertation (Chapter 2), we define what is meant by the term “non-global regression model”, and we provide a brief review of the current literature associated with such models. In particular, we focus on their advantages and disadvantages in terms of their statistical properties. Because there are some weaknesses in the existing non-global regression models, we propose the PLTRM. T

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