evaluation measures
Recently Published Documents


TOTAL DOCUMENTS

361
(FIVE YEARS 95)

H-INDEX

30
(FIVE YEARS 4)

Complexity ◽  
2022 ◽  
Vol 2022 ◽  
pp. 1-10
Author(s):  
Karime Chahuán-Jiménez ◽  
Rolando Rubilar-Torrealba ◽  
Hanns de la Fuente-Mella

Sharpe’s ratio is the most widely used index for establishing an order of priority for the portfolios to which the investor has access, and the purpose of this investigation is to verify that Sharpe’s ratio allows decisions to be made in investment portfolios considering different financial market conditions. The research is carried out by autoregressive model (AR) of the financial series of returns using Sharpe’s ratio for evaluations looking over the priority of financial assets which the investor can access while observing the effects that can cause autocorrelated series in evaluation measures for financial assets. The results presented in this study confirm the hypothesis proposed in which Sharpe’s ratio allows decisions to be made in the selection of investment portfolios under normal conditions thanks to the definition of a robustness function, whose empirical estimation shows an average 73% explanation of the variance in the degradation of the Spearman coefficient for each of the performance measures; however, given the presence of autocorrelation in the financial series of returns, this similarity is broken.


Author(s):  
Mohammad Zoynul Abedin ◽  
Chi Guotai ◽  
Petr Hajek ◽  
Tong Zhang

AbstractIn small business credit risk assessment, the default and nondefault classes are highly imbalanced. To overcome this problem, this study proposes an extended ensemble approach rooted in the weighted synthetic minority oversampling technique (WSMOTE), which is called WSMOTE-ensemble. The proposed ensemble classifier hybridizes WSMOTE and Bagging with sampling composite mixtures to guarantee the robustness and variability of the generated synthetic instances and, thus, minimize the small business class-skewed constraints linked to default and nondefault instances. The original small business dataset used in this study was taken from 3111 records from a Chinese commercial bank. By implementing a thorough experimental study of extensively skewed data-modeling scenarios, a multilevel experimental setting was established for a rare event domain. Based on the proper evaluation measures, this study proposes that the random forest classifier used in the WSMOTE-ensemble model provides a good trade-off between the performance on default class and that of nondefault class. The ensemble solution improved the accuracy of the minority class by 15.16% in comparison with its competitors. This study also shows that sampling methods outperform nonsampling algorithms. With these contributions, this study fills a noteworthy knowledge gap and adds several unique insights regarding the prediction of small business credit risk.


BMJ Open ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. e048203
Author(s):  
Nessa Millet ◽  
Hilary J McDermott ◽  
Fehmidah Munir ◽  
Charlotte L Edwardson ◽  
Esther L Moss

IntroductionCervical cancer treatment can have life changing sequelae and be associated with poor short-term and long-term quality of life. Physical activity (PA; that is, bodily movement) is known to improve health outcomes and quality of life for cancer survivors, both physically and psychologically. To date, no interventions to increase PA following cervical cancer have been evaluated. This study aims to (1) determine the feasibility of conducting a PA intervention after cervical cancer and (2) to explore the acceptability of the programme and evaluation measures.Methods and analysisThe design is a pre study and post study design. Thirty participants aged between 18 and 60 years from the Midlands region, UK, who have completed primary treatment for cervical cancer at least 6 months previously and do not meet the national PA guidelines will be recruited. Identification of potential participants will take place through the University Hospitals of Leicester National Health Service (NHS) Trust. Participants will receive an intervention focused on increasing PA through the provision of education, action planning, goal setting, problem solving and self-monitoring of PA behaviour, particularly steps per day. Device assessed PA and questionnaires will be completed at baseline, week 6, week 12 and week 24. Feasibility will be assessed in terms of recruitment, retention, attrition, completion of measures and intervention compliance, for which specific feasibility criteria have been established. The process evaluation will explore the experiences and acceptability of the intervention components and evaluation measures.Ethics and disseminationEthical approval has been granted by the West of Scotland Research Ethics Committee 1 for this study. Results will inform intervention refinement for the design of a definitive pilot trial. These results will be disseminated via peer-reviewed publications and international conferences while input from a patient and public involvement (PPI) group will inform effective ways to circulate results among the wider community.Trial registration numberISRCTN16349793, Registered 30 September 2020.


Webology ◽  
2021 ◽  
Vol 19 (1) ◽  
pp. 70-82
Author(s):  
Zeina Hassan Razaq

Securing any communication system where important data may be transmitted through the channel is a very crucial issue. One of the good solutions in providing security for the speech is to use speech scrambling techniques. The chaotic system used in security has properties that make it a good choice for scrambling speech signal and the optimisation algorithm can provide a perfect performance when used to enhance the hybrid of more than one method. In this paper, we suggest a system that uses an optimisation method, namely, particle swarm optimisation. The evaluation measures prove that the output of the optimisation method has better performance among the methods used in the comparison, including chaotic maps and hybrid chaotic maps.


Author(s):  
Jos Hornikx ◽  
Annemarie Weerman ◽  
Hans Hoeken

According to Mercier and Sperber (2009, 2011, 2017), people have an immediate and intuitive feeling about the strength of an argument. These intuitive evaluations are not captured by current evaluation methods of argument strength, yet they could be important to predict the extent to which people accept the claim supported by the argument. In an exploratory study, therefore, a newly developed intuitive evaluation method to assess argument strength was compared to an explicit argument strength evaluation method (the PAS scale; Zhao et al., 2011), on their ability to predict claim acceptance (predictive validity) and on their sensitivity to differences in the manipulated quality of arguments (construct validity). An experimental study showed that the explicit argument strength evaluation performed well on the two validity measures. The intuitive evaluation measure, on the other hand, was not found to be valid. Suggestions for other ways of constructing and testing intuitive evaluation measures are presented.


Author(s):  
Hariom Pandya ◽  
Brijesh Bhatt

The usage and amount of information available on the internet increase over the past decade. This digitization leads to the need for automated answering system to extract fruitful information from redundant and transitional knowledge sources. Such systems are designed to cater the most prominent answer from this giant knowledge source to the user’s query using natural language understanding (NLU) and thus eminently depends on the Question-answering(QA) field. Question answering involves but not limited to the steps like mapping of user’s question to pertinent query, retrieval of relevant information, finding the best suitable answer from the retrieved information etc. The current improvement of deep learning models evince compelling performance improvement in all these tasks. In this review work, the research directions of QA field are analyzed based on the type of question, answer type, source of evidence-answer, and modeling approach. This detailing followed by open challenges of the field like automatic question generation, similarity detection and, low resource availability for a language. In the end, a survey of available datasets and evaluation measures is presented.


2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 559-559
Author(s):  
Patricia Oh ◽  
Kathy Black

Abstract The Global Network of Age-friendly Cities and Communities has grown steadily over the past decade across the United States, however surprisingly little is known regarding their accomplishments to date. We utilized content analysis to assess the progress reported by American age-friendly communities (n = 30) that joined by end of year 2015 using the Age-Friendly Community Evidence-based Tool with expanded program evaluation measures including health equity as defined by the World Health Organization. We employed deductive analytic techniques to assess reported community performance in eleven thematic areas across the range of structures and processes that characterize age-friendly efforts. We found strong evidence in the areas of leadership and governance, harnessed resources, application of age-friendly framework, and in multisector collaboration as well as reported provisions. All of the communities reported health equity aims, particularly in promoting accessible physical environments and social inclusion efforts. Our analysis further revealed areas for continued improvement.


2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 859-859
Author(s):  
Teresa Paniagua ◽  
Virginia Fernández-Fernández ◽  
MªÁngeles Molina Martínez

Abstract Introduction COVID-19 pandemic has had a psychological impact on the eldest population. The aim is to analyse whether there are differences depending on the emotional regulation profile shown by a group of older people 6 months before the pandemic and the depressive symptomatology of these people at the same time, during home confinement and 8 months later. Method: Longitudinal study, sample of people over 65, three evaluation measures: WAVE1 (6 months before COVID-19,N=305;M=73.63;58.9% women), WAVE2 (house confinement;N=151;M=73.14;59.6% women) and WAVE3 (8 months later;N=91;M=72.62;64.70% women). We measured depressive symptomatology (CES-D; Radloff, 1977) and nine emotional regulation strategies (CERQ-S; Garnefski et al., 2001; Carvajal et al., 2020), with which 3 clusters were preset (after dendogram inspection and K means analysis). Three mean difference analyses (one-factor ANOVA) were performed taking as factor profiles and as outcomes variables depression in each wave. Results profile 1, people use adaptive cognitive-emotional regulation strategies; profile 2, those with low levels of strategies (adaptive and maladaptive); profile 3, high scores in maladaptive strategies. Statistically significant differences between profiles 1 and 3, in the pre-confinement depression variable (F'2,91=6.18;p=.00) and during confinement (F'2,91=4.02;p=.02). Profile 3 higher depressive symptomatology (x̄1=17.16;x̄2=16.80) than 1 (x̄1=8.41;x̄2=9.65). Differences between profile 1 and 2 and 3 in depression 8 months after confinement (F’2,91=4.02;p=.02). Profile 1 lower levels of depression (x̄3=98.00) than 2 (x̄3=15.78) and 3 (x̄3=14.20). Profiles explain 12.3%, 8.4% and 12.5% of the depression variance in each wave. Conclusions a “protected profile” (1), a “medium-term vulnerable profile” (2) and a “vulnerable profile” (3) to the development of depressive symptomatology.


2021 ◽  
Author(s):  
◽  
Daniel Wayne Crabtree

<p>This thesis investigates the refinement of web search results with a special focus on the use of clustering and the role of queries. It presents a collection of new methods for evaluating clustering methods, performing clustering effectively, and for performing query refinement. The thesis identifies different types of query, the situations where refinement is necessary, and the factors affecting search difficulty. It then analyses hard searches and argues that many of them fail because users and search engines have different query models. The thesis identifies best practice for evaluating web search results and search refinement methods. It finds that none of the commonly used evaluation measures for clustering meet all of the properties of good evaluation measures. It then presents new quality and coverage measures that satisfy all the desired properties and that rank clusterings correctly in all web page clustering situations. The thesis argues that current web page clustering methods work well when different interpretations of the query have distinct vocabulary, but still have several limitations and often produce incomprehensible clusters. It then presents a new clustering method that uses the query to guide the construction of semantically meaningful clusters. The new clustering method significantly improves performance. Finally, the thesis explores how searches and queries are composed of different aspects and shows how to use aspects to reduce the distance between the query models of search engines and users. It then presents fully automatic methods that identify query aspects, identify underrepresented aspects, and predict query difficulty. Used in combination, these methods have many applications — the thesis describes methods for two of them. The first method improves the search results for hard queries with underrepresented aspects by automatically expanding the query using semantically orthogonal keywords related to the underrepresented aspects. The second method helps users refine hard ambiguous queries by identifying the different query interpretations using a clustering of a diverse set of refinements. Both methods significantly outperform existing methods.</p>


Sign in / Sign up

Export Citation Format

Share Document