Relevant bibliographies by topics / Prediction / Dissertations / Theses
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Dissertations / Theses on the topic 'Prediction'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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1

Carrión, Brännström Robin. "Aggregating predictions using Non-Disclosed Conformal Prediction." Thesis, Uppsala universitet, Statistiska institutionen, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-385098.

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When data are stored in different locations and pooling of such data is not allowed, there is an informational loss when doing predictive modeling. In this thesis, a new method called Non-Disclosed Conformal Prediction (NDCP) is adapted into a regression setting, such that predictions and prediction intervals can be aggregated from different data sources without interchanging any data. The method is built upon the Conformal Prediction framework, which produces predictions with confidence measures on top of any machine learning method. The method is evaluated on regression benchmark data sets u
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Miller, Mark Daniel. "Entangled predictive brain : emotion, prediction and embodied cognition." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/33218.

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How does the living body impact, and perhaps even help constitute, the thinking, reasoning, feeling agent? This is the guiding question that the following work seeks to answer. The subtitle of this project is emotion, prediction and embodied cognition for good reason: these are the three closely related themes that tie together the various chapters of the following thesis. The central claim is that a better understanding of the nature of emotion offers valuable insight for understanding the nature of the so called 'predictive mind', including a powerful new way to think about the mind as embod
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Björsell, Joachim. "Long Range Channel Predictions for Broadband Systems : Predictor antenna experiments and interpolation of Kalman predictions." Thesis, Uppsala universitet, Signaler och System, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-281058.

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The field of wireless communication is under massive development and the demands on the cellular system, especially, are constantly increasing as the utilizing devices are increasing in number and diversity. A key component of wireless communication is the knowledge of the channel, i.e, how the signal is affected when sent over the wireless medium. Channel prediction is one concept which can improve current techniques or enable new ones in order to increase the performance of the cellular system. Firstly, this report will investigate the concept of a predictor antenna on new, extensive measure
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Bramlet, John. "Earthquake prediction and earthquake damage prediction /." Connect to resource, 1996. http://hdl.handle.net/1811/31764.

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Greco, Antonino. "The role of task relevance in the modulation of brain dynamics during sensory predictions." Doctoral thesis, Università degli studi di Trento, 2021. http://hdl.handle.net/11572/307050.

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Associative learning is a fundamental ability biological systems possess in order to adapt to a nonstationary environment. One of the core aspects of associative learning theoretical frameworks is that surprising events drive learning by signalling the need to update the system’s beliefs about the probability structure governing stimuli associations. Specifically, the central neural system generates internal predictions to anticipate the causes of its perceptual experience and compute a prediction error to update its generative model of the environment, an idea generally known as the predictiv
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Kock, Peter. "Prediction and predictive control for economic optimisation of vehicle operation." Thesis, Kingston University, 2013. http://eprints.kingston.ac.uk/35861/.

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Truck manufacturers are currently under pressure to reduce pollution and cost of transportation. The cost efficient way to reduce CO[sub]2 and cost is to reduce fuel consumption by adaptation of the vehicle speed to the driving conditions - by heuristic knowledge or mathematical optimisation. Due to their experience, professional drivers are capable of driving with great efficiency in terms of fuel consumption. The key research question addressed in this work is the comparison of the fuel efficiency for an unassisted drive by an experienced professional driver versus an enhanced drive using dr
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Andeta, Jemal Ahmed. "Road-traffic accident prediction model : Predicting the Number of Casualties." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-20146.

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Efficient and effective road traffic prediction and management techniques are crucial in intelligent transportation systems. It can positively influence road advancement, safety enhancement, regulation formulation, and route planning to save living things in advance from road traffic accidents. This thesis considers road safety by predicting the number of casualties if an accident occurs using multiple traffic accident attributes. It helps individuals (drivers) or traffic offices to adjust and control their contributions for the occurrence of an accident before emerging it. Three candidate alg
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Peterson, Ashley Thomas. "Cavitation prediction." Thesis, University of Cambridge, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.612813.

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Åkermark, Alexander, and Mattias Hallefält. "Churn Prediction." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-41236.

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Churn analysis is an important tool for companies as it can reduce the costs that are related to customer churn. Churn prediction is the process of identifying users before they churn, this is done by implementing methods on collected data in order to find patterns that can be helpful when predicting new churners in the future.The objective of this report is to identify churners with the use of surveys collected from different golfclubs, their members and guests. This was accomplished by testing several different supervised machine learning algorithms in order to find the different classes and to s
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Jahedpari, Fatemeh. "Artificial prediction markets for online prediction of continuous variables." Thesis, University of Bath, 2016. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.690730.

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In this dissertation, we propose an online machine learning technique – named Artificial Continuous Prediction Market (ACPM) – to predict the value of a continuous variable by (i) integrating a set of data streams from heterogeneous sources with time varying compositions such as changing the quality of data streams, (ii) integrating the results of several analysis models for each data source when the most suitable model for a given data source is not known a priori, (iii) dynamically weighting the prediction of each analysis model and data source to form the system prediction. We adapt the con
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11

Cai, Xun Ph D. Massachusetts Institute of Technology. "Transforms for prediction residuals based on prediction inaccuracy modeling." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/109003.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 157-162).<br>In a typical transform-based image and video compression system, an image or a video frame is predicted from previously encoded information. The prediction residuals are encoded with transforms. With a proper choice of the transform, a large amount of the residual energy compacts into a small number of transform coefficients. This is known as the energy compaction property. Giv
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Shrestha, Rakshya. "Deep soil mixing and predictive neural network models for strength prediction." Thesis, University of Cambridge, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.607735.

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13

Lönnbark, Carl. "On Risk Prediction." Doctoral thesis, Umeå universitet, Nationalekonomi, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-22200.

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This thesis comprises four papers concerning risk prediction. Paper [I] suggests a nonlinear and multivariate time series model framework that enables the study of simultaneity in returns and in volatilities, as well as asymmetric effects arising from shocks. Using daily data 2000-2006 for the Baltic state stock exchanges and that of Moscow we find recursive structures with Riga directly depending in returns on Tallinn and Vilnius, and Tallinn on Vilnius. For volatilities both Riga and Vilnius depend on Tallinn. In addition, we find evidence of asymmetric effects of shocks arising in Moscow an
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14

Chan, Pee Yuaw. "Software reliability prediction." Thesis, City, University of London, 1986. http://openaccess.city.ac.uk/18127/.

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Two methods are proposed to find the maximum likelihood parameter estimates of a number of software reliability models. On the basis of the results from analysing 7 sets of real data, these methods are found to be both efficient and reliable. The simple approach of adapting software reliability predictions by Keiller and Littlewood (1984) can produce improved predictions, but at the same time, introduces a lot of internal noise into the adapted predictions. This is due to the fact that the adaptor is a joined-up function. An alternative adaptive procedure, which involves the parametric spline
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Samee, Farman. "Options with Prediction." Thesis, University of Manchester, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.516360.

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Cai, Changqing. "Personal preference prediction." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ61879.pdf.

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Tardieu, Giliane. "Thermal conductivity prediction." Thesis, Georgia Institute of Technology, 1987. http://hdl.handle.net/1853/10014.

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Cuff, James Andrew. "Protein structure prediction." Thesis, University of Oxford, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.365685.

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Care, Matthew Anthony. "Deleterious SNP prediction." Thesis, University of Leeds, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.496547.

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Anderson, O. E. "Grammatical error prediction." Thesis, University of Cambridge, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.595506.

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In this thesis, we investigate methods for automatic detection, and to some extent correction, of grammatical errors. The evaluation is based on manual error annotation in the Cambridge Learner Corpus (CLC), and automatic or semi-automatic annotation of error corpora is one possible application, but the methods are also applicable in other settings, for instance to give learners feedback on their writing or in a proofreading tool used to prepare texts for publication. Apart from the CLC, we use the British National Corpus (BNC) to get a better model of correct usage, WordNet for semantic relat
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21

Wright, David R. "Software reliability prediction." Thesis, City University London, 2001. http://openaccess.city.ac.uk/8387/.

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This thesis presents some extensions to existing methods of software reliability estimation and prediction. Firstly, we examine a technique called 'recalibration' by means of which many existing software reliability prediction algorithms assess past predictive performance in order to improve the accuracy of current reliability predictions. This existing technique for forecasting future failure times of software is already quite general. Indeed, whenever your predictions are produced in the form of time-to-failure distributions, successively as more actual failure times are observed, you can ap
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22

Yates, Amanda Marie. "Prediction of sepsis." Thesis, University of the West of England, Bristol, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.429692.

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Steel, Donald. "Software reliability prediction." Thesis, Abertay University, 1990. https://rke.abertay.ac.uk/en/studentTheses/4613ff72-9650-4fa1-95d1-1a9b7b772ee4.

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The aim of the work described in this thesis was to improve NCR's decision making process for progressing software products through the development cycle. The first chapter briefly describes the software development process at NCR, detailing documentation review and software testing techniques. The objectives and reasons for investigating software reliability models as a tool in the decision making process are outlined. There follows a short review of software reliability models, with the Littlewood and Verrall Bayesian model considered in detail. The difficulties in using this model to obtain
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24

Luo, Meng. "Frost Depth Prediction." Thesis, North Dakota State University, 2014. https://hdl.handle.net/10365/27488.

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The purpose of this research project is to develop a model that is able to accurately predict frost depth on a particular date, using available information. Frost depth prediction is useful in many applications in several domains. For example in agriculture, knowing frost depth early is crucial for farmers to determine when and how deep they should plant. In this study, data is collected primarily from NDAWN(North Dakota AgriculturalWeather Network) Fargo station for historical soil depth temperature and weather information. Lasso regression is used to model the frost depth. Since soil t
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Aghi, Nawar, and Ahmad Abdulal. "House Price Prediction." Thesis, Högskolan Kristianstad, Fakulteten för naturvetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hkr:diva-20945.

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This study proposes a performance comparison between machine learning regression algorithms and Artificial Neural Network (ANN). The regression algorithms used in this study are Multiple linear, Least Absolute Selection Operator (Lasso), Ridge, Random Forest. Moreover, this study attempts to analyse the correlation between variables to determine the most important factors that affect house prices in Malmö, Sweden. There are two datasets used in this study which called public and local. They contain house prices from Ames, Iowa, United States and Malmö, Sweden, respectively.The accuracy of the
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Vlasák, Pavel. "Exhange Rates Prediction." Master's thesis, Vysoká škola ekonomická v Praze, 2009. http://www.nusl.cz/ntk/nusl-76388.

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The aim of this thesis is to examine the dependence of the exchange rate movement on the core fundamentals of the economy in the long term, as well as to test the validity of selected indicators of technical analysis in the short term. The dependence of the exchange rate will be examined using correlation and the discussed fundamentals are the main macroeconomic indicators, such as GDP, short-term interest rates and money base M2. In the part, which deals with the technical analysis, I will test the two groups of indicators, namely trend indicators and oscillators. From the first group it will
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Lönnbark, Carl. "On risk prediction /." Umeå : Institutionen för nationalekonomi, Umeå universitet, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-22200.

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28

Ge, Esther. "The query based learning system for lifetime prediction of metallic components." Thesis, Queensland University of Technology, 2008. https://eprints.qut.edu.au/18345/4/Esther_Ting_Ge_Thesis.pdf.

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This research project was a step forward in developing an efficient data mining method for estimating the service life of metallic components in Queensland school buildings. The developed method links together the different data sources of service life information and builds the model for a real situation when the users have information on limited inputs only. A practical lifetime prediction system was developed for the industry partners of this project including Queensland Department of Public Works and Queensland Department of Main Roads. The system provides high accuracy in practice where n
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Ge, Esther. "The query based learning system for lifetime prediction of metallic components." Queensland University of Technology, 2008. http://eprints.qut.edu.au/18345/.

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This research project was a step forward in developing an efficient data mining method for estimating the service life of metallic components in Queensland school buildings. The developed method links together the different data sources of service life information and builds the model for a real situation when the users have information on limited inputs only. A practical lifetime prediction system was developed for the industry partners of this project including Queensland Department of Public Works and Queensland Department of Main Roads. The system provides high accuracy in practice where n
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Oleksandra, Shovkun. "Some methods for reducing the total consumption and production prediction errors of electricity: Adaptive Linear Regression of Original Predictions and Modeling of Prediction Errors." Thesis, Linnéuniversitetet, Institutionen för matematik (MA), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-34398.

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Balance between energy consumption and production of electricityis a very important for the electric power system operation and planning. Itprovides a good principle of effective operation, reduces the generation costin a power system and saves money. Two novel approaches to reduce thetotal errors between forecast and real electricity consumption wereproposed. An Adaptive Linear Regression of Original Predictions (ALROP)was constructed to modify the existing predictions by using simple linearregression with estimation by the Ordinary Least Square (OLS) method.The Weighted Least Square (WLS) me
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Pesquita, Ana. "The social is predictive : human sensitivity to attention control in action prediction." Thesis, University of British Columbia, 2016. http://hdl.handle.net/2429/59076.

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Observing others is predicting others. Humans have a natural tendency to make predictions about other people’s future behavior. This predisposition sits at the basis of social cognition: others become accessible to us because we are able to simulate their internal states, and in this way make predictions about their future behavior (Blakemore & Decety, 2001). In this thesis, I examine prediction in the social realm through three main contributions. The first contribution is of a theoretical nature, the second is methodological, and the third contribution is empirical. On the theoretical plane,
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Horton, Sara Jane. "Refining the prediction of childhood diabetes using insulin autoantibodies : disease predictive idiotypes." Thesis, University of Exeter, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.418545.

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Yang, Ziyi. "Monitoring and predicting railway subsidence using InSAR and time series prediction techniques." Thesis, University of Birmingham, 2015. http://etheses.bham.ac.uk//id/eprint/6377/.

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Improvements in railway capabilities have resulted in heavier axle loads and higher speed operations, which increase the dynamic loads on the track. As a result, railway subsidence has become a threat to good railway performance and safe railway operation. The author of this thesis provides an approach for railway performance assessment through the monitoring and prediction of railway subsidence. The InSAR technique, which is able to monitor railway subsidence over a large area and long time period, was selected for railway subsidence monitoring. Future trends of railway subsidence should also
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Bangalore, Narendranath Rao Amith Kaushal. "Online Message Delay Prediction for Model Predictive Control over Controller Area Network." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/78626.

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Today's Cyber-Physical Systems (CPS) are typically distributed over several computing nodes communicating by way of shared buses such as Controller Area Network (CAN). Their control performance gets degraded due to variable delays (jitters) incurred by messages on the shared CAN bus due to contention and network overhead. This work presents a novel online delay prediction approach that predicts the message delay at runtime based on real-time traffic information on CAN. It leverages the proposed method to improve control quality, by compensating for the message delay using the Model Predictive
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Baker, Kristen. "Examining how attention and prediction modulate visual perception: A predictive coding view." Thesis, Queensland University of Technology, 2022. https://eprints.qut.edu.au/235895/1/Kristen%2BBaker%2BThesis%282%29.pdf.

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This thesis investigated the relationship between prediction and attention in visual perception by recording electrophysiological brain responses. Visual paradigms were implemented using various manipulations of stimuli (shapes, neutral faces, and emotional faces), types of attention (spatial, featural, and emotion-guided), and prior precision of spatial location (low and high). This thesis found that during the early stages of visual processing prediction error signalling consistently occurs, with information then diverging into the associated brain regions for further processing for informat
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Chen, Yutao. "Algorithms and Applications for Nonlinear Model Predictive Control with Long Prediction Horizon." Doctoral thesis, Università degli studi di Padova, 2018. http://hdl.handle.net/11577/3421957.

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Fast implementations of NMPC are important when addressing real-time control of systems exhibiting features like fast dynamics, large dimension, and long prediction horizon, as in such situations the computational burden of the NMPC may limit the achievable control bandwidth. For that purpose, this thesis addresses both algorithms and applications. First, fast NMPC algorithms for controlling continuous-time dynamic systems using a long prediction horizon have been developed. A bridge between linear and nonlinear MPC is built using partial linearizations or sensitivity update. In order to
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Dahlgren, Lindström Adam. "Structured Prediction using Voted Conditional Random FieldsLink Prediction in Knowledge Bases." Thesis, Umeå universitet, Institutionen för datavetenskap, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-140692.

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Knowledge bases are useful in the validation of automatically extracted information, and for hypothesis selection during the extraction process. Building knowledge bases is a dfficult task and the process is bound to miss facts. Therefore, the existence of facts can be estimated using link prediction, i.e., by solving the structured prediction problem.It has been shown that combining directly observable features with latent features increases performance. Observable features include, e.g., the presence of another chain of facts leading to the same end point. Latent features include, e.g, prope
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Iqbal, Ammar Tanange Rakesh Virk Shafqat. "Vehicle fault prediction analysis : a health prediction tool for heavy vehicles /." Göteborg : IT-universitetet, Chalmers tekniska högskola och Göteborgs universitet, 2006. http://www.ituniv.se/w/index.php?option=com_itu_thesis&Itemid=319.

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GAO, HONGLIANG. "IMPROVING BRANCH PREDICTION ACCURACY VIA EFFECTIVE SOURCE INFORMATION AND PREDICTION ALGORITHMS." Doctoral diss., University of Central Florida, 2008. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3286.

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Modern superscalar processors rely on branch predictors to sustain a high instruction fetch throughput. Given the trend of deep pipelines and large instruction windows, a branch misprediction will incur a large performance penalty and result in a significant amount of energy wasted by the instructions along wrong paths. With their critical role in high performance processors, there has been extensive research on branch predictors to improve the prediction accuracy. Conceptually a dynamic branch prediction scheme includes three major components: a source, an information processor, and a predict
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Löfström, Tuwe. "On Effectively Creating Ensembles of Classifiers : Studies on Creation Strategies, Diversity and Predicting with Confidence." Doctoral thesis, Stockholms universitet, Institutionen för data- och systemvetenskap, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-116683.

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An ensemble is a composite model, combining the predictions from several other models. Ensembles are known to be more accurate than single models. Diversity has been identified as an important factor in explaining the success of ensembles. In the context of classification, diversity has not been well defined, and several heuristic diversity measures have been proposed. The focus of this thesis is on how to create effective ensembles in the context of classification. Even though several effective ensemble algorithms have been proposed, there are still several open questions regarding the role d
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Zhu, Zheng. "A Unified Exposure Prediction Approach for Multivariate Spatial Data: From Predictions to Health Analysis." University of Cincinnati / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin155437434818942.

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Darwiche, Aiman A. "Machine Learning Methods for Septic Shock Prediction." Diss., NSUWorks, 2018. https://nsuworks.nova.edu/gscis_etd/1051.

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Sepsis is an organ dysfunction life-threatening disease that is caused by a dysregulated body response to infection. Sepsis is difficult to detect at an early stage, and when not detected early, is difficult to treat and results in high mortality rates. Developing improved methods for identifying patients in high risk of suffering septic shock has been the focus of much research in recent years. Building on this body of literature, this dissertation develops an improved method for septic shock prediction. Using the data from the MMIC-III database, an ensemble classifier is trained to identify
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Mehdi, Muhammad Sarim. "Trajectory Prediction for ADAS." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/21891/.

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A novel pipeline is presented for unsupervised trajectory prediction. As part of this research, numerous techniques are investigated for trajectory prediction of dynamic obstacles from an egocentric perspective (driver’s per- spective). The algorithm takes images from a calibrated stereo camera as input or data from a laser scanner and outputs a heat map that describes all possible future locations of that specific 3D object for the next few frames. This research has many applications, most notably for autonomous cars as it allows them to make better driving decisions if they are able t
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Glass, Colin William. "Computational crystal structure prediction /." Zürich : ETH, 2008. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=17852.

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Bäumer, Lars. "Identification in prediction theory." [S.l. : s.n.], 2000. http://deposit.ddb.de/cgi-bin/dokserv?idn=959725504.

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Ibarria, Lorenzo. "Geometric Prediction for Compression." Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/16162.

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This thesis proposes several new predictors for the compression of shapes, volumes and animations. To compress frames in triangle-mesh animations with fixed connectivity, we introduce the ELP (Extended Lorenzo Predictor) and the Replica predictors that extrapolate the position of each vertex in frame $i$ from the position of each vertex in frame $i-1$ and from the position of its neighbors in both frames. For lossy compression we have combined these predictors with a segmentation of the animation into clips and a synchronized simplification of all frames in a clip. To compress 2D and 3D st
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Schelin, Lina. "Spatial sampling and prediction." Doctoral thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-53286.

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This thesis discusses two aspects of spatial statistics: sampling and prediction. In spatial statistics, we observe some phenomena in space. Space is typically of two or three dimensions, but can be of higher dimension. Questions in mind could be; What is the total amount of gold in a gold-mine? How much precipitation could we expect in a specific unobserved location? What is the total tree volume in a forest area? In spatial sampling the aim is to estimate global quantities, such as population totals, based on samples of locations (papers III and IV). In spatial prediction the aim is to estim
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Rigaldo, Alexis. "Aerodynamics Gust Response Prediction." Thesis, KTH, Flygdynamik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-41506.

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This project presents the work performed within the aerodynamics department of Airbus Operation SAS inToulouse through a ve months master thesis. This department works with the industrialization and the use of tools developed by laboratories to perform CFD aerodynamic simulations. The primary purpose of the present work was to support the development of gust analysis methods based on CFD. A new gust model has been developed and integrated to the aerodynamic solver elsA.This solver has been used in order to compute the unsteady aerodynamic simulations for both gust loads and forced motions with
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Fredette, Marc. "Prediction of recurrent events." Thesis, University of Waterloo, 2004. http://hdl.handle.net/10012/1142.

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In this thesis, we will study issues related to prediction problems and put an emphasis on those arising when recurrent events are involved. First we define the basic concepts of frequentist and Bayesian statistical prediction in the first chapter. In the second chapter, we study frequentist prediction intervals and their associated predictive distributions. We will then present an approach based on asymptotically uniform pivotals that is shown to dominate the plug-in approach under certain conditions. The following three chapters consider the prediction of recurrent events. The
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Nordfors, Per. "Prediction of Code Lifetime." Thesis, Linköpings universitet, Statistik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-135060.

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There are several previous studies in which machine learning algorithms are used to predict how fault-prone a piece of code is. This thesis takes on a slightly different approach by attempting to predict how long a piece of code will remain unmodified after being written (its “lifetime”). This is based on the hypothesis that frequently modified code is more likely to contain weaknesses, which may make lifetime predictions useful for code evaluation purposes. In this thesis, the predictions are made with machine learning algorithms which are trained on open source code examples from GitHub. Two
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