Relevant bibliographies by topics / Behaviour scoring

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Behaviour scoring'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Behaviour scoring"

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Bravo, Cristián, Lyn C. Thomas, and Richard Weber. "Improving credit scoring by differentiating defaulter behaviour." Journal of the Operational Research Society 66, no. 5 (2015): 771–81. http://dx.doi.org/10.1057/jors.2014.50.

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Rebitschek, Felix G., Gerd Gigerenzer, Ariane Keitel, Sarah Sommer, Christian Groß, and Gert G. Wagner. "Acceptance of criteria for health and driver scoring in the general public in Germany." PLOS ONE 16, no. 4 (2021): e0250224. http://dx.doi.org/10.1371/journal.pone.0250224.

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Numerous health insurers offer bonus programmes that score customers’ health behaviour, and car insurers offer telematics tariffs that score driving behaviour. In many countries, however, only a minority of customers participate in these programmes. In a population-representative survey of private households in Germany (N = 2,215), we study the acceptance of the criteria (features) on which the scoring programmes are based: the features for driver scoring (speed, texting while driving, time of driving, area of driving, accelerating and braking behaviour, respectively) and for health scoring (walking distance per day, sleeping hours per night, alcohol consumption, weight, participation in recommended cancer screenings, smoking status). In a second step, we model participants’ acceptance of both programmes with regard to the underlying feature acceptance. We find that insurers in Germany rarely use the features which the participants consider to be the most relevant and justifiable, that is, smoking status for health scoring and smartphone use for driver scoring. Heuristic models (fast-and-frugal trees) show that programme acceptance depends on the acceptance of a few features. These models can help to understand customers’ preferences and to design scoring programmes that are based on scientific evidence regarding behaviours and factors associated with good health and safe driving and are thus more likely to be accepted.
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Fritz, Sebastian, and Detlef Hosemann. "Restructuring the credit process: behaviour scoring for german corporates." International Journal of Intelligent Systems in Accounting, Finance & Management 9, no. 1 (2000): 9–21. http://dx.doi.org/10.1002/(sici)1099-1174(200003)9:1<9::aid-isaf168>3.0.co;2-q.

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Ngesan, Mohd Riduan, and Syed Sobri Syed Zubir. "Assessing Nighttime Place Identity using Measurable Indicator Scoring Technique." Asian Journal of Behavioural Studies 3, no. 12 (2018): 23. http://dx.doi.org/10.21834/ajbes.v3i12.119.

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This paper is a comparative study of place identity of nighttime urban public parks between Shah Alam that was built in 1957 and Putrajaya in 1999. This study used four research domains that form place identity adapted from Relph, 1976 and Cheshmehzangi, 2012. The method of this study involves the behavior mapping survey and the questionnaire survey. The data were then analysed using Measurable Indicator Scoring Technique (Karim, 2008) to ensure constant comparative process by creating analytic codes. It is hope that the findings from this study would help to improve the place identity and functions of future nighttime urban public parks.Keywords: Nighttime place identity; urban public park; Measurable Indicator Scoring TechniqueeISSN 2398-4295 © 2018. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open-access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning &amp; Surveying, Universiti Teknologi MARA, Malaysia.
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Burón, P., S. Al-Halabí, E. Díaz-Mesa, et al. "Suicide attempts and suicide ideation in adolescents: SDQ scores in the Spanish sample of “saving and empowering young lives in Europe” (SEYLE) project." European Psychiatry 26, S2 (2011): 1609. http://dx.doi.org/10.1016/s0924-9338(11)73313-2.

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IntroductionBehaviour disorders in adolescents are a risk factor associated with suicidal behavior.AimTo examine the distribution of the Strengths and Difficulties Questionnaire (SDQ) scores in the Spanish sample of adolescents from the “Saving and Empowering Young Lives in Europe” (SEYLE) project and study the differences according to the gender and the relationship with both suicide attempts (SA) and suicidal ideation (SI).Method875 pupils from 12 secondary schools sited in Asturias (Spain) [50.7% males; mean age (SD) =14.5 (0.72)] were assessed through the SDQ and Paykel Suicide Scale (PSS).ResultsNo significant differences were found in the SDQ total score by gender, but were found (p&lt; 0.001) in some subscales as emotional symptoms (t=-6.769) (women scoring higher), hyperactivity (t=3.283) and prosocial (t=5.260) (men scoring higher). Regarding PSS, 3.1% tried to take their life during past six months. No significant differences were found in SA by gender but were found (p&lt; 0.050) for the thought that life not worth (t=-3.597), women scoring higher, and about wish to be dead (t=-2.630), men scoring higher. Previous SA were significant related (p&lt; 0.001) with SDQ total score (X2=38,437), emotional symptoms (X2=25,528), hyperactivity (X2=13,572) and behaviour disorders (X2=7,505). SI was significant related (p&lt; 0.001) with SDQ total score (X2=38,437), emotional symptoms (X2=31,077), behaviour disorders (X2=33,011), peer problems (X2=35,161) and prosocial behavior (X2=17,978).ConclusionSA and SI were related with difficulties (SDQ criteria), mainly on emotional symptoms and behaviour disorders. Prevention strategies in high risk groups are likely to become increasingly important.
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BLACKWELL, MARTIN, and CHRIS SYKES. "The assignment of credit limits with a behaviour-scoring system." IMA Journal of Management Mathematics 4, no. 1 (1992): 73–80. http://dx.doi.org/10.1093/imaman/4.1.73.

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Marqués, A. I., V. García, and J. S. Sánchez. "Exploring the behaviour of base classifiers in credit scoring ensembles." Expert Systems with Applications 39, no. 11 (2012): 10244–50. http://dx.doi.org/10.1016/j.eswa.2012.02.092.

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Diaz-Lundahl, Sofia, Selina Hellestveit, Solveig Marie Stubsjøen, Clare J. Phythian, Randi Oppermann Moe, and Karianne Muri. "Intra- and Inter-Observer Reliability of Qualitative Behaviour Assessments of Housed Sheep in Norway." Animals 9, no. 8 (2019): 569. http://dx.doi.org/10.3390/ani9080569.

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This study tested the reliability of a Qualitative Behavioural Assessment (QBA) protocol developed for the Norwegian Sheep House (FåreBygg) project. The aim was to verify whether QBA scores were consistent between different observers, i.e., inter-observer reliability, and between scorings of the same observers on different time points, i.e., intra-observer reliability. Six trained observers, including two veterinary students, two animal welfare inspectors and two sheep farmers observed sheep in 16 videos, and independently scored 14 pre-defined behavioural descriptors on visual analogue scales (VAS). The procedure was repeated one week after the first scoring session. QBA scores were analysed using Principal Component Analysis. Inter- and intra-observer agreement was assessed using Kendall’s coefficient of concordance (W). Principal component 1 (PC 1) and 2 (PC 2) combined explained &gt;60% of the total variation in the QBA scores in both scoring sessions. PC 1 (44.5% in sessions 1 and 2) ranged from the positive descriptors calm, content, relaxed and friendly to the negative descriptors uneasy, vigilant and fearful, and was therefore labelled mood. PC 2 (18% in session 1, 16.6% in session 2) ranged from bright to dejected and apathetic, and was therefore labelled arousal. Kendall’s coefficient of concordance of PC 1 for all observers was high in the two scoring sessions (W = 0.87 and 0.85, respectively), indicating good inter-observer reliability. For PC 2, the agreement for all observers was moderate in both video sessions (W = 0.45 and 0.65). The intra-observer agreement was very high for all observers for PC 1 (W &gt; 0.9) except for one, where the agreement was considered to be high (W = 0.89). For PC 2, Kendall’s coefficient was very high for the veterinary students and interpreted as moderate for the two farmers and welfare inspectors. This study indicates that the QBA approach and the terms included in the Fårebygg protocol were reliable for assessing video recordings of sheep behaviour when applied by trained observers, regardless of whether they were a veterinary student, animal welfare inspector or sheep farmer. Further work is needed to examine the reliability of the QBA protocol when tested on-farms for sheep managed under Norwegian housing systems.
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Frank, Cairina E., Kathy N. Speechley, Jennifer J. Macnab, and M. Karen Campbell. "Infants Born Large for Gestational Age and Developmental Attainment in Early Childhood." International Journal of Pediatrics 2018 (2018): 1–7. http://dx.doi.org/10.1155/2018/9181497.

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Objectives. To investigate if an association exists between being born large for gestational age (LGA) and verbal ability or externalizing behaviour problems at ages 4-5 years. Method. A secondary analysis was conducted using the National Longitudinal Survey of Children and Youth, including singleton births in 2004-2005 followed till 4-5 years (n=1685). LGA was defined as a birth weight &gt; 90th percentile. Outcomes included poor verbal ability (scoring &lt; 15th percentile on the Revised Peabody Picture Vocabulary Test) and externalizing behaviour problems (scoring &gt; 90th percentile on externalizing behaviour scales). Multivariable logistic regression with longitudinal standardized funnel weights and bootstrapping estimation were used. Results. Infants born LGA were not found to be at increased risk for poor verbal ability (aOR: 1.16 [0.49,2.72] and aOR: 0.83 [0.37,1.87] for girls and boys, resp.) or externalizing behaviour problems (aOR: 1.24 [0.52,2.93] and aOR: 1.24 [0.66,2.36] for girls and boys, resp.). Social factors were found to impact developmental attainment. Maternal smoking led to an increased risk for externalizing behaviour problems (aOR: 3.33 [1.60,6.94] and aOR: 2.12 [1.09,4.13] for girls and boys, resp.). Conclusion. There is no evidence to suggest that infants born LGA are at increased risk for poor verbal ability or externalizing behaviour problems.
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Honess, Paul E., Jessica L. Gimpel, Sarah E. Wolfensohn, and Georgia J. Mason. "Alopecia Scoring: The Quantitative Assessment of Hair Loss in Captive Macaques." Alternatives to Laboratory Animals 33, no. 3 (2005): 193–206. http://dx.doi.org/10.1177/026119290503300308.

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Many captive animals show forms of pelage loss that are absent in wild or free-living con-specifics, which result from grooming or plucking behaviours directed at themselves or at other individuals. For instance, dorsal hair loss in primates such as rhesus macaques ( Macaca mulatta) in research facilities, results from excessive hair-pulling or over-grooming by cage-mates. This behaviour appears to be associated with stress, and is controllable to some extent with environmental enrichment. Quantifying alopecia in primates (as in many species) is therefore potentially useful for welfare assessment. A simple system for scoring alopecia was developed and its reliability was tested. Study 1 showed high interobserver reliability between two independent scorers in assessing the state of monkeys’ coats from photographs. Study 2 showed that there were no significant differences between the scores derived from photographs and from direct observations. Thus, where hair loss due to hair pulling exists in captive primates, this scoring system provides an easy, rapid, and validated quantitative method, for use in assessing the success of attempts to reduce it via improved husbandry. In the future, such scoring systems might also prove useful for quantifying barbering in laboratory rodents.
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Dissertations / Theses on the topic "Behaviour scoring"

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Hamilton, Robert. "[Credit] scoring : predicting, understanding and explaining consumer behaviour." Thesis, Loughborough University, 2005. https://dspace.lboro.ac.uk/2134/13053.

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This thesis stems from my research into the broad area of (credit) scoring and the predicting, understanding and explaining of consumer behaviour. This research started at the Univers1ty of Edinburgh on an ESRC funded project in 1988. This work, which is being submitted as the partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough Unvers1ty, consists of an introductory chapter and a selection of papers published 1991 - 2001 (inclusive). The papers address some of the key issues and areas of interest and concern arising from the rapidly evolving and expanding credit (card) market and the highly competitive nature of the credit industry. These features were particularly evident during the late 1980's and throughout the 90's Chapter One provides a general background to the research and outlines some of the key (practical) issues involved in building a (credit) scorecard Additionally, it provides a brief summary of each of the research papers appearing in full in Chapters 2- 9 (inclusive) and ends with some general limitations and conclusions. The research papers appearing in Chapters 2-9 inclusive) are all concerned with predicting, understanding and explaining different types of consumer behaviour in relation to the use of credit cards. For example discriminating between 'GOOD' and 'BAD' repayers of credit card debt on the basis of different definitions of good and bad, the identification of 'slow payers' using different statistical methods; examining the characteristics of credit card users and non-users, and identifying the characteristics of credit card holders most likely to return their credit card.
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Schmidt, Wagner. "Passivo contingente em instituição financeira: proposta de análise de risco utilizando os modelos Credit Scoring e Behaviour Scoring." Pontifícia Universidade Católica de São Paulo, 2010. https://tede2.pucsp.br/handle/handle/1437.

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Made available in DSpace on 2016-04-25T18:39:35Z (GMT). No. of bitstreams: 1 Wagner Schmidt.pdf: 8727051 bytes, checksum: 9669cd75306633dfdd1a2d712ce4d2a3 (MD5) Previous issue date: 2010-10-28<br>This study is the result of the present observation of the movement of civil lawsuits that are growing every day on the market of financial institutions. Nowadays, especially in financial institutions, significant civil lawsuits has been a concern of executives. The main objective of this study is to propose a model of risk management for contingent liabilities in financial institutions, since the difficulty of managing such numbers in the deal result. This is an adaptation of the instruments used in the management of credit risk for the legal area. The models used are the Behaviour Scoring and Credit Scoring. The first model is based on the curve behavioral processes, in this work are denominated like variables. These variables are known industry products offered by financial institutions. On a second level is taken into account the reasons, known as triggering events that led to the civil suits. The second model, Credit Scoring, based on a statistical study of values, which serve as the basis in determining the historical losses. The proposed study is to assist the risk management of these liabilities, eliminating the subjectivity of analysis and allowing greater speed in information. The present results prove that it is possible to use the instruments in question to the risk management of contingent liabilities, reducing the subjectivity of analysis, as greater adherence to criteria and faster responses for managers. The top ten products analyzed shows the results of Credit Scores, for the respective taxable events, termed here as Behaviour Scores. This work, in addition to demonstrating the applicability of the models Credit Scoring and Behavior Scoring also allows us to expand this study to other fields of activities, such as telecommunications, energy, companies that handle large volumes of civil lawsuits, as well as expanded discussion of risk allocation of contingent liability for the product<br>Este estudo é o resultado da observação atual do movimento de ações cíveis que vem crescendo a cada dia no mercado de instituições financeiras. Nos dias atuais, principalmente nas instituições financeiras, volumes significativos de ações judiciais cíveis tem sido motivo de preocupação dos executivos. O principal objetivo deste estudo é propor um modelo de gestão de risco para passivos contingentes nas instituições financeiras, visto a dificuldade de gestão desses números dentro do resultado do negócio. Trata-se de uma adaptação dos instrumentos utilizados na área de gestão de risco de crédito para a área jurídica. Os modelos utilizados em questão são o Behaviour Scoring e o Credit Scoring. O primeiro modelo baseia-se na curva comportamental dos processos, que neste trabalho denominam-se como variáveis. Estas variáveis são os conhecidos produtos ofertados pela indústria das instituições financeiras. Em um segundo nível é levado em consideração os motivos, ou seja, fatos geradores que geraram as ações cíveis. O segundo modelo, o Credit Scoring, baseia-se em um estudo estatístico de valores, os quais servirão de base na apuração das perdas históricas. A proposta do estudo é auxiliar a gestão do risco desses passivos, eliminando a subjetividade de análise e permitindo maior velocidade nas informações. Os resultados obtidos neste trabalho provam que é possível utilizar os instrumentos em questão para a gestão do risco do passivo contingente, diminuindo a subjetividade de análise, visto maior aderência nos critérios e respostas mais rápidas para os gestores. O top ten de produtos analisados mostra os resultados dos Credit Scores, para os respectivos fatos geradores, denominado neste trabalho como Behaviour Scores. Este trabalho, além de evidenciar a aplicabilidade dos modelos Credit Scoring e Behaviour Scoring, também permite expandir este estudo para outros ramos de atividades, como telefonia, energia, empresas que operam com grandes volumes de ações cíveis, além de expandir discussões como alocação de risco de passivo contingente por produto
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Till, Robert John. "Predictive behavioural models in credit scoring and retail banking." Thesis, Imperial College London, 2002. http://hdl.handle.net/10044/1/7984.

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Karlsson, Erik. "Behavior recording with the scoring program MouseClick : A study in cross platform and precise timing developing." Thesis, Uppsala universitet, Informationssystem, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-132079.

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This thesis will deal with problems and solutions of cross-platform developing using MoNo framework as a replacement of Microsoft .NET framework on Linux and Mac OS-X platforms. It will take in account matters such as limitations in the filesystem to problems with deploying released programs. It will also deal with demands of precise timing and the need of efficient code on precise tasks to construct a program used for creating data from recordings of animals. These animals is set to perform a task, for example exploring a labyrinth or running on a rod, and it is all recorded on video. These videos are later reviewed by an observer which transcripts the recordings into data based on predefined behaviors and the time and frequency with which the animal is expressing them.
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OlLIVEIRA, NETO Rosalvo Ferreira de. "COMOVI: um framework para transformação de dados em aplicações de credit behavior scoring baseado no desenvolvimento dirigido por modelos." Universidade Federal de Pernambuco, 2015. https://repositorio.ufpe.br/handle/123456789/17330.

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Submitted by Fabio Sobreira Campos da Costa (fabio.sobreira@ufpe.br) on 2016-07-12T12:11:15Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Tese_Rosalvo_Neto_CIN_2015.pdf: 7674683 bytes, checksum: 99037c704450a9a878bcbe93ab8b392d (MD5)<br>Made available in DSpace on 2016-07-12T12:11:15Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Tese_Rosalvo_Neto_CIN_2015.pdf: 7674683 bytes, checksum: 99037c704450a9a878bcbe93ab8b392d (MD5) Previous issue date: 2015-12-11<br>CAPEs<br>A etapa de pré-processamento em um projeto de descoberta do conhecimento é custosa, em geral, consome cerca de 50 a 80% do tempo total de um projeto. É nesta etapa que um banco de dados relacional é transformado para aplicação de um algoritmo de mineração de dados. A transformação dos dados nesta etapa é uma tarefa complexa, uma vez que exige uma forte integração entre projetistas de banco de dados e especialistas do domínio da aplicação. Os frameworks que buscam sistematizar a etapa de transformação dos dados encontrados na literatura apresentam limitações significativas quando aplicados a soluções comportamentais, como Credit Behavior Scoring. Estas soluções visam a auxiliar as instituições financeiras a decidirem sobre a concessão de crédito aos consumidores com base no risco das solicitações. Este trabalho propõe um framework baseado no Desenvolvimento Dirigido por Modelos para sistematizar esta etapa em soluções de Credit Behavior Scoring. Ele é composto por um meta-modelo que mapeia os conceitos do domínio e um conjunto de regras de transformações. As três principais contribuições do framework proposto são: 1) aumentar o poder discriminatório da solução, através da construção de novas variáveis que maximizam o conteúdo estatístico da informação do domínio; 2) reduzir o tempo da transformação dos dados através da geração automática de código e 3) permitir que profissionais e pesquisadores de Inteligência Artificial e Estatística realizem a transformação dos dados sem o auxílio de especialistas de Banco de Dados. Para validar o framework proposto, dois estudos comparativos foram realizados. Primeiro, um estudo comparando o desempenho entre os principais frameworks existentes na literatura e o framework proposto foi realizado em duas bases de dados. Uma base de dados de um conhecido benchmark de uma competição internacional organizada pela PKDD, e outra obtida de uma das maiores empresas de varejo do Brasil, que possui seu próprio cartão de crédito. Os frameworks RelAggs e Validação de Múltiplas Visões Baseado em Correção foram escolhidos como representantes das abordagens proposicional e mineração de dados relacional, respectivamente. A comparação foi realizada através do processo de validação cruzada estratificada, para definir os intervalos de confiança para a avaliação de desempenho. Os resultados mostram que o framework proposto proporciona um desempenho equivalente ou superior aos principais framework existentes, medido pela área sob a curva ROC, utilizando uma rede neural MultiLayer Perceptron, K vizinho mais próximos e Random Forest como classificadores, com um nível de confiança de 95%. O segundo estudo verificou a redução de tempo proporcionada pelo framework durante a transformação dos dados. Para isso, sete times compostos por estudantes de uma universidade brasileira mensuraram o tempo desta atividade com e sem o framework proposto. O teste pareado Wilcoxon Signed-Rank mostrou que o framework proposto reduz o tempo de transformação com um nível de confiança de 95%.<br>The pre-processing stage in knowledge discovery projects is costly, generally taking between 50 and 80% of total project time. It is in this stage that data in a relational database are transformed for applying a data mining technique. This stage is a complex task that demands from database designers a strong interaction with experts who have a broad knowledge about the application domain. The frameworks that aim to systemize the data transformation stage have significant limitations when applied to behavior solutions such as the Credit Behavior Scoring solutions. Their goal is help financial institutions to decide whether to grant credit to consumers based on the credit risk of their requests. This work proposes a framework based on the Model Driven Development to systemize this stage in Credit Behavioral Scoring solutions. It is composed by a meta-model which maps the domain concepts and a set of transformation rules. This work has three main contributions: 1) improving the discriminant power of data mining techniques by means of the construction of new input variables, which embed new knowledge for the technique; 2) reducing the time of data transformation using automatic code generation and 3) allowing artificial intelligence and statistics modelers to perform the data transformation without the help of database experts. In order to validate the proposed framework, two comparative studies were conducted. First, a comparative study of performance between the main existing frameworks found in literature and the proposed framework applied to two databases was performed. One database from a known benchmark of an international competition organized by PKDD, and another one obtained from one of the biggest retail companies from Brazil, that has its own private label credit card. The RelAggs and Correlation-based Multiple View Validation frameworks were chosen as representatives of the propositional and relational data mining approaches, respectively. The comparison was carried out through by a 10-fold stratified cross-validation process with ten stratified parts in order to define the confidence intervals. The results show that the proposed framework delivers a performance equivalent or superior to those of existing frameworks, for the evaluation of performance measured by the area under the ROC curve, using a Multilayer Perceptron neural network, k-nearest neighbors and Random Forest as classifiers, with a confidence level of 95%. The second comparative study verified the reduction of time required for data transformation using the proposed framework. For this, seven teams composed by students from a Brazilian university measured the runtime of this stage with and without the proposed framework. The paired Wilcoxon Signed-Rank’s Test showed that the proposed framework reduces the time of data transformation with a confidence level of 95%.
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Scott, Sybil. "Nonverbal behaviour in the process of the therapeutic interview : an ecosystemic perspective." Diss., 1996. http://hdl.handle.net/10500/17701.

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Communication can be divied into two broad areas namely, the verbal and nonverbal levels. While attention has been paid to nonverbal communication in the literature, few studies address the nonverbal communication that takes place in the natural setting of a therapeutic session. The present study provides such a naturalistic study, where the verbal content of actual therapy sessions are integrated with the nonverbal content to yield a holistic view of the session. An ecosystemic epistemology is adopted in this study, and represents a move away from more traditional approaches to nonverbal behaviour which are largely confined to a positivistic framework of thought and design. Symlog Interaction Scoring is employed as a practical method of assisting observers in distinguishing nonverbal behaviours, which are usually perceived unconsciously, and lifting them into consciousness, allowing this infonnation to be integrated with the meanings and hypotheses generated during therapy. By deliberately including descriptions of nonverbal behaviour, the descriptions of therapy were broadened, thereby providing a more holistic approach to therapy.<br>Psychology<br>M.A. (Clinical Psychology)
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Preto, Ana Figueiredo Costa. "Analyses of default predicted models for a single family loan." Master's thesis, 2016. http://hdl.handle.net/10362/18615.

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This study aims to explore the possibility of a financial entity to produce a predicted model of default. The study aims to compares the performance of an existing model, the FICO and an alternative model, based on cluster analysis method with dataset available. A third option is presented for the analyses of default, which it is the junction of both models. This third method can be implemented in two different ways: the two models agreeing with acceptance of the loan or the two models approving the rejection of the loan.
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Vallam, Rohith Dwarakanath. "Game-Theoretic Analysis of Strategic Behaviour in Networks, Crowds and Classrooms." Thesis, 2014. http://hdl.handle.net/2005/2955.

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Over the past decade, the explosive growth of the Internet has led to a surge of interest to understand and predict aggregate behavior of large number of people or agents, particularly when they are connected through an underlying network structure. Numerous Internet-based applications have emerged that are as diverse as getting micro-tasks executed through online labor markets (also known as crowd sourcing) to acquiring new skills through massively open online courses (also known as MOOCs). However, there has been a major inadequacy in existing studies with respect to evaluating the impact of strategic behavior of the agents participating in such networks, crowds, and classrooms. The primary focus of this doctoral work is to understand the equilibrium behaviour emerging from these real-world, strategic environments by blending ideas from the areas of game theory, graph theory, and optimization, to derive novel solutions to these new-age economic models. In particular, we investigate the following three research challenges: (1) How do strategic agents form connections with one another? Will it ever happen that strategically stable networks are social welfare maximizing as well? (2) How do we design mechanisms for eliciting truthful feedback about an object (perhaps a new product or service or person) from a crowd of strategic raters? What can we tell about these mechanisms when the raters are connected through a social network? (3) How do we incentivize better participation of instructors and students in online edu-cation forums? Can we recommend optimal strategies to students and instructors to get the best out of these forums?
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YU, PAY-WEN, and 尤姵文. "The Scoring Model of Alumni Donation Behavior." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/37777600846686553862.

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博士<br>輔仁大學<br>商學研究所博士班<br>104<br>To propose a practical alumni donor classification model, this study applied customer profitability analysis from relational marketing theory as a basis to investigate the classification of alumni groups by donation profitability using data contained in a university database regarding a large number of university alumni. The ultimate purpose of this study was to provide a new direction for university planning and fundraising strategies. The subject of this case study was a private university in Taiwan, and its alumni database was used to construct an alumni donor type analysis model through the application of four data mining techniques, discriminant analysis, artificial neural network, multivariate adaptive regression splines and support vector machines. This study tries to identify important characteristics of classifying four types of alumni groups: lost alumni without profitability, lost alumni with profitability, retained alumni without profitability, and retained alumni with profitability. The study will compare the classification accuracy if the four classification techniques and suitable strategies can be proposed based on the research findings.
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Jeng, Shou-Li, and 鄭守利. "Building A Credit Behavior Scoring Model by Using Glmnet." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/23877219639652180923.

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碩士<br>輔仁大學<br>應用統計學研究所<br>97<br>Credit scoring and behavioural scoring are statistical application commonly used by banks to decide whether or not to grant a loan to customers. Recent global depressions have led credit-granting institutions to search for more effective ways to attract creditworthy customers and control losses. At the customer management level, these two kinds of risk-scoring methodologies offer an objective approaches to predict delinquency. The recent development of behavioral scorings, differs from traditional scorings, adds more information of the repayment and usage behavior of customers and thus can be used further to forecast long term default probability and to adjust credit limits as parts of for examples the marketing and operational policy. Some classical statistical methods logistic regression was first used and remains the most important methods to build scoring systems. More new methods were proposed based on the idea of statistical learning. A novel statistical learning method called Glmnet (Generalized Linear Models via Elastic-Net) is proposed recently. Glmnet enables the creative idea of lasso to be extended to generalized linear models (GLM). Compared to traditionally GLM, Glmnet can not only provide parameter estimations and variable selections simultaneously but also create a computationally efficient process by an elastic-net algorithm. In our study, Glmnet is first proposed in the modeling of behavioural scorings classification accuracy analysis systems. We also compare the results with ANN (Artificial Neural Network), SVM (Support Vector Machines) and LDA (Linear Discriminant Analysis).
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Books on the topic "Behaviour scoring"

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Finlay, Steven. Credit scoring, response modelling and insurance rating: A practical guide to forecasting consumer behaviour. Palgrave Macmillan, 2010.

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Finlay, Steven. Credit scoring, response modelling and insurance rating: A practical guide to forecasting consumer behaviour. Palgrave Macmillan, 2010.

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Thomas, L. C. Behavioural scoring. University of Edinburgh. Department of Business Studies, 1988.

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Bryant, Brian R. adaptive behavior scale, residential and community: Software scoring and report system. 2nd ed. Pro-ed, 1993.

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Hann, Robert G. Release risk prediction: A test of the Nuffield scoring system. Ministry of the Solicitor General, Programs Branch, 1989.

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Finlay, Steven. Credit scoring, response modeling, and insurance rating: A practical guide to forecasting consumer behavior. 2nd ed. Palgrave Macmillan, 2012.

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Hann, Robert G. Release risk prediction: Testing the Nuffield scoring system for native and female inmates. Ministry of the Solicitor General, Programs Branch, 1989.

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Zdrok, Victoria Alexandrovna. Dr. Z on scoring: How to pick up, seduce, and hook up with hot women. Simon & Schuster, 2008.

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Finlay, S. Credit Scoring, Response Modelling and Insurance Rating: A Practical Guide to Forecasting Consumer Behaviour. Palgrave Macmillan, 2010.

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Figorilli, Michela, Monica Puligheddu, and Raffaele Ferri. Scoring guidelines for sleep-related movements. Edited by Sudhansu Chokroverty, Luigi Ferini-Strambi, and Christopher Kennard. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199682003.003.0010.

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This chapter focuses on available and validated scoring guidelines for sleep-related movements, such as periodic limb movements, alternating legs movements, rhythmic movements, sleep bruxism, sleep myoclonus, and REM behavior disorder. Some scoring methods have recently been updated with the use of computerized and automatic techniques; others are based on old criteria derived from visual analysis of events recorded on paper. Further studies are needed to develop and validate automatic scoring methods and to assess their reliability and usefulness for both research purposes and clinical practice. Moreover, scoring methods and related cut-off values have to be validated, not only against controls, but also in specific populations, such as patients with Parkinson disease and REM behavior disorder.
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Book chapters on the topic "Behaviour scoring"

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Madeira, Sara C., Arlindo L. Oliveira, and Catarina S. Conceição. "A Data Mining Approach to Credit Risk Evaluation and Behaviour Scoring." In Progress in Artificial Intelligence. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-24580-3_25.

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Ertek, Gürdal, Murat Kaya, Cemre Kefeli, Özge Onur, and Kerem Uzer. "Scoring and Predicting Risk Preferences." In Behavior Computing. Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2969-1_9.

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Nishisato, Shizuhiko, Eric J. Beh, Rosaria Lombardo, and Jose G. Clavel. "Scoring and Profiles." In Behaviormetrics: Quantitative Approaches to Human Behavior. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2470-4_7.

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Sharma, Sonam, and Garima Makkar. "Scoring Algorithm Identifying Anomalous Behavior in Enterprise Network." In Data Management, Analytics and Innovation. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5619-7_6.

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Gupta, Anmol, Sanidhya Pandey, Harsh Krishna, Subham Pramanik, and P. Gouthaman. "Behavioural Scoring Based on Social Activity and Financial Analytics." In Inventive Computation and Information Technologies. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4305-4_56.

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Zhang, Defu, Qingshan Chen, and Lijun Wei. "Building Behavior Scoring Model Using Genetic Algorithm and Support Vector Machines." In Computational Science – ICCS 2007. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-72586-2_69.

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Caronongan, Arturo P., and Rafael A. Cabredo. "Modeling User Music Preference Through Usage Scoring and User Listening Behavior for Generating Preferred Playlists." In Principles and Practice of Multi-Agent Systems. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46218-9_5.

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Riley, Jeff. "Evolving Fuzzy Rules for Goal-Scoring Behaviour in Robot Soccer." In Robot Soccer. InTech, 2010. http://dx.doi.org/10.5772/7345.

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Riley, Jeff, and Vic Ciesielski. "Analysing the Difficulty of Learning Goal-Scoring Behaviour for Robot Soccer." In Robotic Soccer. I-Tech Education and Publishing, 2007. http://dx.doi.org/10.5772/5137.

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Hubley, Anita M., and Maeve A. Mangaoang. "Neuropsychological Assessment." In The ITC International Handbook of Testing and Assessment. Oxford University Press, 2016. http://dx.doi.org/10.1093/med:psych/9780199356942.003.0012.

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Neuropsychological assessment involves compiling information about a person’s premorbid or current behaviour and using it to make inferences about his or her brain functioning or to predict behavior. Today, neuropsychological assessment is focused on identifying cognitive deficits associated with different disorders; changes over time; efficacy of treatment; and patient strengths and weaknesses. It is also used to predict functioning, guide rehabilitation planning, and supplement forensic/legal evaluations. Key elements of neuropsychological assessments described in the chapter include history taking; behavioral observations; the testing situation; selection, administration, and scoring of tests; and test standardization and norms. Descriptions of fixed, flexible, and “flexible battery” approaches to testing are provided, as are descriptions of quantitative (norm) and qualitative (process) approaches. Several norming approaches of particular interest to neuropsychological assessment (i.e., continuous norming, equivalent scores, overlapping cell tables) are noted. An overview is provided of a number of commonly assessed areas of neuropsychological functioning.
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Conference papers on the topic "Behaviour scoring"

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Vora, Saransh, Mostafa Shahriari, Stelios C. A. Thomopoulos, Lukas Fischer, and Thomas Hoch. "A scoring algorithm for abnormal traveller behaviour in border crossing areas." In Counterterrorism, Crime Fighting, Forensics, and Surveillance Technologies IV, edited by Henri Bouma, Robert J. Stokes, Yitzhak Yitzhaky, and Radhakrishna Prabhu. SPIE, 2020. http://dx.doi.org/10.1117/12.2573963.

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Riley, Jeff, and Vic Ciesielski. "Analysis of the difficulty of learning goal-scoring behaviour for robot soccer." In the 8th annual conference. ACM Press, 2006. http://dx.doi.org/10.1145/1143997.1144251.

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Spingler, G. "Numerical Modelling of Laser Scoring Line Behaviour for Seamless Passenger Airbag Door Opening." In SAE World Congress & Exhibition. SAE International, 2009. http://dx.doi.org/10.4271/2009-01-0356.

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Waltereit, Marian, Peter Zdankin, Viktor Matkovic, Maximilian Uphoff, and Torben Weis. "Online Driving Behavior Scoring using Wheel Speeds." In 6th International Conference on Vehicle Technology and Intelligent Transport Systems. SCITEPRESS - Science and Technology Publications, 2020. http://dx.doi.org/10.5220/0009215604170424.

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Qing-Shan, Chen, Zhang De-Fu, Wei Li-Jun, and Chen Huo-Wang. "A Modified Genetic Programming for Behavior Scoring Problem." In 2007 IEEE Symposium on Computational Intelligence and Data Mining. IEEE, 2007. http://dx.doi.org/10.1109/cidm.2007.368921.

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Zhang, Rong, Xiaofeng He, Aoying Zhou, and Chaofeng Sha. "Online evaluation re-scoring based on review behavior analysis." In 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). IEEE, 2014. http://dx.doi.org/10.1109/asonam.2014.6921558.

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Kar, Gorkem, Batuhan Asiroglu, and Fatih Sinan Bir. "Scotto: Real-Time Driver Behavior Scoring Using In-Vehicle Data." In 2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring). IEEE, 2019. http://dx.doi.org/10.1109/vtcspring.2019.8746461.

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Liu, Ke, Kin Keung Lai, and Sy-Ming Guu. "Dynamic Credit Scoring on Consumer Behavior Using Fuzzy Markov Model." In 2009 Fourth International Multi-Conference on Computing in the Global Information Technology. IEEE, 2009. http://dx.doi.org/10.1109/iccgi.2009.42.

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Almeida, Fernando, Pedro Henriques Abreu, Nuno Lau, and Luis Paulo Reis. "Automatic extraction of goal-scoring behaviors from soccer matches." In 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2012). IEEE, 2012. http://dx.doi.org/10.1109/iros.2012.6386091.

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"Review Spammer Detection by using Behaviors Based Scoring Methods." In International Conference on Advances in Engineering and Technology. International Institute of Engineers, 2014. http://dx.doi.org/10.15242/iie.e0314158.

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Reports on the topic "Behaviour scoring"

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Filmer, Deon, Ezequiel Molina, and Waly Wane. Identifying Effective Teachers: Lessons from Four Classroom Observation Tools. Research on Improving Systems of Education (RISE), 2020. http://dx.doi.org/10.35489/bsg-rise-wp_2020/045.

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Four different classroom observation instruments—from the Service Delivery Indicators, the Stallings Observation System, the Classroom Assessment Scoring System, and the Teach classroom observation instrument—were implemented in about 100 schools across four regions of Tanzania. The research design is such that various combinations of tools were administered to various combinations of teachers, so these data can be used to explore the commonalities and differences in the behaviors and practices captured by each tool, the internal properties of the tools (for example, how stable they are across enumerators, or how various indicators relate to one another), and how variables collected by the various tools compare to each other. Analysis shows that inter-rater reliability can be low, especially for some of the subjective ratings; principal components analysis suggests that lower-level constructs do not map neatly to predetermined higher-level ones and suggest that the data have only a few dimensions. Measures collected during teacher observations are associated with student test scores, but patterns differ for teachers with lower versus higher subject content knowledge.
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