scholarly journals A new re-encoding ECOC using reject option

2020 ◽  
Vol 50 (10) ◽  
pp. 3090-3100 ◽  
Author(s):  
Lei Lei ◽  
Yafei Song ◽  
Xi Luo
Keyword(s):  
Loss Function ◽  
Operating Characteristic ◽  
Classification Model ◽  
Threshold Values ◽  
Reject Option ◽  
Roc Convex Hull ◽  
Low Degree ◽  
New Variant ◽  
Cost Sensitive Classification ◽  
The Cost

Abstract When training base classifier by ternary Error Correcting Output Codes (ECOC), it is well know that some classes are ignored. On this account, a non-competent classifier emerges when it classify an instance whose real label does not belong to the meta-subclasses. Meanwhile, the classic ECOC dichotomizers can only produce binary outputs and have no capability of rejection for classification. To overcome the non-competence problem and better model the multi-class problem for reducing the classification cost, we embed reject option to ECOC and present a new variant of ECOC algorithm called as Reject-Option-based Re-encoding ECOC (ROECOC). The cost-sensitive classification model and cost-loss function based on Receiver Operating Characteristic (ROC) curve are built respectively. The optimal reject threshold values are obtained by combing the condition to be met for minimizing the loss function and the ROC convex hull. In so doing, reject option (t1, t2) provides a three-symbol output to make dichotomizers more competent and ROECOC more universal and practical for cost-sensitive classification issue. Experimental results on two kinds of datasets show that our scheme with low-degree freedom of initialized ECOC can effectively enhance accuracy and reduce cost.

Cost-Sensitive Classification Using Decision Trees, Boosting and MetaCost

2011 ◽  
pp. 27-53 ◽  
Author(s):  
Kai Ming Ting
Keyword(s):  
Decision Trees ◽  
Major Contributor ◽  
Expected Cost ◽  
Cost Criterion ◽  
Instance Weighting ◽  
New Variant ◽  
Cost Sensitive Classification ◽  
Boosting Algorithms ◽  
The Cost ◽  
Minimum Expected Cost

This chapter reports results obtained from a series of studies on costsensitive classification using decision trees, boosting algorithms, and MetaCost which is a recently proposed procedure that converts an errorbased algorithm into a cost-sensitive algorithm. The studies give rise to new variants of algorithms designed for cost-sensitive classification, and provide insights into the strength and weaknesses of the algorithms. First, we describe a simple and effective heuristic of converting an error-based decision tree algorithm into a cost-sensitive one via instance weighting. The cost-sensitive version performs better than the error-based version that employs a minimum expected cost criterion during classification. Second, we report results from a study on four variants of cost-sensitive boosting algorithms. We find that boosting can be simplified for costsensitive classification. A new variant which excludes a factor used in ordinary boosting has an advantage of producing smaller trees and different trees for different scenarios; while it performs comparably to ordinary boosting in terms of cost. We find that the minimum expected cost criterion is the major contributor to the improvement of all cost-sensitive adaptations of ordinary boosting. Third, we reveal a limitation of MetaCost. We find that MetaCost retains only part of the performance of the internal classifier on which it relies. This occurs for both boosting and bagging as its internal classifier.

Influence of trends in the development of the Russian agro-industrial complex on the introduction of integrated reporting of agricultural enterprises

2021 ◽  
pp. 6-14
Author(s):  
Mary Konstantinovna Dzhikia
Keyword(s):  
Milk Production ◽  
Russian Federation ◽  
Rural Areas ◽  
Industrial Complex ◽  
Main Program ◽  
Threshold Values ◽  
Integrated Reporting ◽  
Agricultural Enterprises ◽  
The Russian Federation ◽  
The Cost

In this article, the main program documents for the development of the Russian agro-industrial complex are considered, the dynamics of the cost of agricultural gross output is revealed, the factor analysis of milk production in the Russian Federation is carried out, the factors of increasing milk production are determined, the risks in the field of food security are considered, the trends of changes in the engineering infrastructure in rural areas are revealed, the decrease in the import of basic food and the excess of the threshold values of indicators of food independence (selfsufficiency) are revealed.) Of the Russian Federation in 2019 for basic food products. Based on the analysis of the state of agriculture in Russia, the trends that led to the need for the introduction of integrated reporting for agricultural enterprises are highlighted.

Cost-Sensitive Learning in Medicine

2011 ◽  
pp. 57-75
Author(s):  
Alberto Freitas ◽  
Pavel Brazdil ◽  
Altamiro Costa-Pereira
Keyword(s):  
Diagnostic Tests ◽  
False Negative ◽  
Cost Sensitive Learning ◽  
Safety Issues ◽  
Misclassification Costs ◽  
Misclassification Errors ◽  
Cost Sensitive Classification ◽  
Human Costs ◽  
The Cost ◽  
Specific Diagnostic Test

This chapter introduces cost-sensitive learning and its importance in medicine. Health managers and clinicians often need models that try to minimize several types of costs associated with healthcare, including attribute costs (e.g. the cost of a specific diagnostic test) and misclassification costs (e.g. the cost of a false negative test). In fact, as in other professional areas, both diagnostic tests and its associated misclassification errors can have significant financial or human costs, including the use of unnecessary resource and patient safety issues. This chapter presents some concepts related to cost-sensitive learning and cost-sensitive classification and its application to medicine. Different types of costs are also present, with an emphasis on diagnostic tests and misclassification costs. In addition, an overview of research in the area of cost-sensitive learning is given, including current methodological approaches. Finally, current methods for the cost-sensitive evaluation of classifiers are discussed.

scholarly journals Mixed-Degree Spherical Simplex-Radial Cubature Kalman Filter

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Shiyuan Wang ◽  
Yali Feng ◽  
Shukai Duan ◽  
Lidan Wang
Keyword(s):  
Kalman Filter ◽  
Computational Complexity ◽  
Kalman Filters ◽  
Order Moment ◽  
Low Degree ◽  
Cubature Kalman Filter ◽  
Highly Nonlinear ◽  
Spherical Simplex ◽  
The Cost ◽  
High Degree

Conventional low degree spherical simplex-radial cubature Kalman filters often generate low filtering accuracy or even diverge for handling highly nonlinear systems. The high-degree Kalman filters can improve filtering accuracy at the cost of increasing computational complexity; nevertheless their stability will be influenced by the negative weights existing in the high-dimensional systems. To efficiently improve filtering accuracy and stability, a novel mixed-degree spherical simplex-radial cubature Kalman filter (MSSRCKF) is proposed in this paper. The accuracy analysis shows that the true posterior mean and covariance calculated by the proposed MSSRCKF can agree accurately with the third-order moment and the second-order moment, respectively. Simulation results show that, in comparison with the conventional spherical simplex-radial cubature Kalman filters that are based on the same degrees, the proposed MSSRCKF can perform superior results from the aspects of filtering accuracy and computational complexity.

scholarly journals Tree Cover Estimation in Global Drylands from Space Using Deep Learning

2020 ◽  
Vol 12 (3) ◽  
pp. 343 ◽  
Author(s):  
Emilio Guirado ◽  
Domingo Alcaraz-Segura ◽  
Javier Cabello ◽  
Sergio Puertas-Ruíz ◽  
Francisco Herrera ◽  
...  
Keyword(s):  
Forest Cover ◽  
Global Scale ◽  
Classification Model ◽  
Tree Cover ◽  
System Modelling ◽  
Earth System ◽  
Visual Interpretation ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
The Cost

Accurate tree cover mapping is of paramount importance in many fields, from biodiversity conservation to carbon stock estimation, ecohydrology, erosion control, or Earth system modelling. Despite this importance, there is still uncertainty about global forest cover, particularly in drylands. Recently, the Food and Agriculture Organization of the United Nations (FAO) conducted a costly global assessment of dryland forest cover through the visual interpretation of orthoimages using the Collect Earth software, involving hundreds of operators from around the world. Our study proposes a new automatic method for estimating tree cover using artificial intelligence and free orthoimages. Our results show that our tree cover classification model, based on convolutional neural networks (CNN), is 23% more accurate than the manual visual interpretation used by FAO, reaching up to 79% overall accuracy. The smallest differences between the two methods occurred in the driest regions, but disagreement increased with the percentage of tree cover. The application of CNNs could be used to improve and reduce the cost of tree cover maps from the local to the global scale, with broad implications for research and management.

scholarly journals A Computationally Efficient Method for Probabilistic Parameter Threshold Analysis for Health Economic Evaluations

2020 ◽  
Vol 40 (5) ◽  
pp. 669-679
Author(s):  
Zoë Pieters ◽  
Mark Strong ◽  
Virginia E. Pitzer ◽  
Philippe Beutels ◽  
Joke Bilcke
Keyword(s):  
Monte Carlo ◽  
Cost Effectiveness ◽  
Cost Effective ◽  
Routine Vaccination ◽  
Threshold Analysis ◽  
Threshold Values ◽  
Threshold Probability ◽  
Monte Carlo Approach ◽  
Effectiveness Model ◽  
The Cost

Background. Threshold analysis is used to determine the threshold value of an input parameter at which a health care strategy becomes cost-effective. Typically, it is performed in a deterministic manner, in which inputs are varied one at a time while the remaining inputs are each fixed at their mean value. This approach will result in incorrect threshold values if the cost-effectiveness model is nonlinear or if inputs are correlated. Objective. To propose a probabilistic method for performing threshold analysis, which accounts for the joint uncertainty in all input parameters and makes no assumption about the linearity of the cost-effectiveness model. Methods. Three methods are compared: 1) deterministic threshold analysis (DTA); 2) a 2-level Monte Carlo approach, which is considered the gold standard; and 3) a regression-based method using a generalized additive model (GAM), which identifies threshold values directly from a probabilistic sensitivity analysis sample. Results. We applied the 3 methods to estimate the minimum probability of hospitalization for typhoid fever at which 3 different vaccination strategies become cost-effective in Uganda. The threshold probability of hospitalization at which routine vaccination at 9 months with catchup campaign to 5 years becomes cost-effective is estimated to be 0.060 and 0.061 (95% confidence interval [CI], 0.058–0.064), respectively, for 2-level and GAM. According to DTA, routine vaccination at 9 months with catchup campaign to 5 years would never become cost-effective. The threshold probability at which routine vaccination at 9 months with catchup campaign to 15 years becomes cost-effective is estimated to be 0.092 (DTA), 0.074 (2-level), and 0.072 (95% CI, 0.069–0.075) (GAM). GAM is 430 times faster than the 2-level approach. Conclusions. When the cost-effectiveness model is nonlinear, GAM provides similar threshold values to the 2-level Monte Carlo approach and is computationally more efficient. DTA provides incorrect results and should not be used.

Receiver operating characteristic analysis of milk lactosefor identification of mastitis in buffaloes

2016 ◽  
Author(s):  
T. K. Patbandha ◽  
K. Ravikala ◽  
B. R. Maharana ◽  
Rupal Pathak ◽  
S. Marandi ◽  
...  
Keyword(s):  
Receiver Operating Characteristic ◽  
Roc Analysis ◽  
Operating Characteristic ◽  
Positive Likelihood Ratio ◽  
Threshold Values ◽  
Characteristic Analysis ◽  
Statistical Tool ◽  
Milk Samples ◽  
Diagnostic Indicator ◽  
Receiver Operating

Receiver operating characteristic (ROC) analysis is a simple statistical tool used to classify a diagnostic indicator in terms of area under a ROC curve (AUC) and to develop potential threshold values of a diagnostic indicator. Milk lactose was analyzed by ROC analysis to see its accuracy to discriminate infected and healthy udder quarters, and to develope an optimum threshold value along with corresponding sensitivity (Se), specificity (Sp) and positive likelihood ratio (LR+) value. Data for the present study comprised of 1516 milk samples collected from Jaffrabadi buffaloes. Milk lactose was estimated by milk analyzer ‘LACTOSCAN’ and further samples were checked for sub-clinical mastitis by California mastitis test (CMT). The threshold values of milk lactose for identification of moderate and severe infection were found to be 5.31g% (Se, 58.82%; Sp, 58.28%) and 5.23g% (Se, 70.97%; Sp, 64.41%), respectively by ROC analysis. Milk samples with lactose content below 5.31g% were 1.41 times more likely come from moderately infected quarters (LR+ = 1.41); whereas, below 5.23g% were 1.99 times more likely come from severely infected quarters (LR+ = 1.99). The overall accuracy of milk lactose for discrimination of normal quarters from moderately infected quarters was 64% (AUC=0.64) and from severely infected quarters was 72% (AUC=0.72) (P<0.001). Thus, the present study indicated that milk lactose classified mastitic and healthy udder quarters in Jaffrabadi buffaloes with moderate accuracy.

scholarly journals Stratified Threshold Values of QuantiFERON Assay for Diagnosing Tuberculosis Infection in Immunocompromised Populations

2011 ◽  
Vol 2011 ◽  
pp. 1-9 ◽  
Author(s):  
Haruyuki Ariga ◽  
Hideaki Nagai ◽  
Atsuyuki Kurashima ◽  
Yoshihiko Hoshino ◽  
Syunsuke Shoji ◽  
...  
Keyword(s):  
Operating Characteristic ◽  
Characteristic Curve ◽  
Latent Tuberculosis ◽  
Absolute Number ◽  
Threshold Values ◽  
Risk Of Progression ◽  
Healthy Control ◽  
Ifn Γ ◽  
The Relationship ◽  
Hiv Negative

Background. The detection of latent tuberculosis (TB) is essential for TB control, but T-cell assay might be influenced by degree of immunosuppression. The relationship between immunocompetence and interferon (IFN)-γ response in QuantiFERON-TB Gold (QFT) is uncertain, especially in HIV-negative populations.Methods and Results. QFT has been performed for healthy subjects and TB suspected patients. Of 3017 patients, 727 were diagnosed as pulmonary TB by culture. The absolute number of blood lymphocyte in TB patients was significantly associated with QFT. Definitive TB patients were divided into eight groups according to lymphocyte counts. For each subgroup, receiver operating characteristic curve analysis was conducted from 357 healthy control subjects. The optimal cut-off for the patient group with adequate lymphocyte counts was found, but this was reduced for lymphocytopenia.Conclusions. The lymphocyte count was positively associated with QFT. Positive criteria should be calibrated in consideration of cell-mediated immunocompetence and risk of progression to active TB.

scholarly journals СОВЕРШЕНСТВОВАНИЕ ГИДРОМЕЛИОРАТИВНЫХ МАШИНС  АВТОМАТИЗАЦИЕЙ ПРОЦЕССА ПОЛИВА

2019 ◽  
Author(s):  
A. Akhtyamov ◽  
A. Ryazantsev ◽  
O. Gavrilina ◽  
A. Boyko ◽  
S. Borychev ◽  
...  
Keyword(s):  
Low Cost ◽  
Economic Effect ◽  
Hydraulic Drive ◽  
Cost Savings ◽  
Practical Implementation ◽  
High Productivity ◽  
Low Degree ◽  
The Cost ◽  
Positive Results ◽  
Horizontal Arrangement

Целью исследования являлось теоретическое обоснование и практическая реализация нового способа полива гидромелиоративной машиной Фрегат с гидроприводом на сложном рельефе с минимальными затратами на модернизацию и энергозатратами. Объектом исследования является экспериментальный кранзадатчик скорости, устанавливаемый на гидромелиоративную машину. Исследования проводились в сравнении с показателями машин серийного производства. В ходе исследования было установлено, что существующая технология полива не отвечает необходимым требованиям гидромелиорации и имеет низкую степень экономической эффективности. Предлагаемая технология полива решает вопрос неравномерного распределения влаги по площади, повышает урожайность и снижает стоимость обслуживания машины вследствие уменьшения числа поломок. Имеющиеся модернизации дождевальной машины (ДМ) Фрегат , позволяющие работать по предлагаемой технологии, сложны по конструкции, ненадежны и имеют относительно высокую стоимость модернизации и сезонного обслуживания. С целью увеличения экономии средств и упрощения процесса модернизации серийных машин был разработан и протестирован кранзадатчик скорости, позволяющий снизить риск эрозии почв, застревания колес тележек и, тем самым, простой машины с необходимостью ее ремонта. Главной особенностью экспериментального краназадатчика скорости является его горизонтальное расположение относительно тележки. Два плеча с увеличенной длиной позволяют задавать поливную норму путем касания вех в начале каждого сектора, где необходимо сменить скорость движения машины. Таким образом, происходит регулирование поливной нормы, выдаваемой машиной при ее движении по орошаемой площади. Получившийся экономический эффект позволяет утверждать о положительных результатах в проведенных исследованияхThe aim of the research is the theoretical justification and practical implementation of the new method of irrigation irrigation and drainage machines Frigat with hydraulic drive for complex tasks of modernization and energy consumption. The object of the study is an experimental speedadjusting crane installed on a water reclamation machine. The studies were conducted in comparison with indicators of machine production. In the course of research it was found that the existing technology does not meet the requirements of irrigation and drainage and has a low degree of economic efficiency. The issue of uneven distribution of the owner by area, high productivity and low cost of maintenance is being addressed. DM Frigat, which allows you to work on the proposed technologies, does not require the cost of modernization and seasonal maintenance. In order to increase cost savings and develop new models of machines, a speed control crane has been developed and tested to reduce the risk of machine destruction. The operation of the trolley is the horizontal arrangement of the trolley. The speed of the machine can be increased. Thus, regulation of the irrigation rate occurs. The resulting economic effect allows us to argue about the positive results in the studies

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