• Title/Summary/Keyword: Asymmetric loss

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Support Vector Quantile Regression Using Asymmetric e-Insensitive Loss Function

  • Shim, Joo-Yong;Seok, Kyung-Ha;Hwang, Chang-Ha;Cho, Dae-Hyeon
    • Communications for Statistical Applications and Methods
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    • v.18 no.2
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    • pp.165-170
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    • 2011
  • Support vector quantile regression(SVQR) is capable of providing a good description of the linear and nonlinear relationships among random variables. In this paper we propose a sparse SVQR to overcome a limitation of SVQR, nonsparsity. The asymmetric e-insensitive loss function is used to efficiently provide sparsity. The experimental results are presented to illustrate the performance of the proposed method by comparing it with nonsparse SVQR.

Optimization of a Thermally Asymmetric Rectangular Fin: Based on Fixed Fin Height

  • Kang, Hyung-Suk
    • International Journal of Air-Conditioning and Refrigeration
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    • v.13 no.3
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    • pp.145-151
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    • 2005
  • A thermally asymmetric straight rectangular fin is analysed and optimized using the two-dimensional separation of variables method. The optimum heat loss is presented as a function of bottom to top Biot number ratio, fin base length and top Biot number. Decreasing rate of the optimum fin length with the increase of the fin base length is listed. The optimum fin tip length is shown as a function of bottom to top Biot number ratio, fin base length and tip to top Biot number ratio. One of the results shows that the optimum heat loss and the actual optimum fin length decrease while the optimum fin tip length increases as the fin base length increases.

Bayesian Estimation of the Reliability Function of the Burr Type XII Model under Asymmetric Loss Function

  • Kim, Chan-Soo
    • Communications for Statistical Applications and Methods
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    • v.14 no.2
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    • pp.389-399
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    • 2007
  • In this paper, Bayes estimates for the parameters k, c and reliability function of the Burr type XII model based on a type II censored samples under asymmetric loss functions viz., LINEX and SQUAREX loss functions are obtained. An approximation based on the Laplace approximation method (Tierney and Kadane, 1986) is used for obtaining the Bayes estimators of the parameters and reliability function. In order to compare the Bayes estimators under squared error loss, LINEX and SQUAREX loss functions respectively and the maximum likelihood estimator of the parameters and reliability function, Monte Carlo simulations are used.

Optimization of an Asymmetric Trapezoidal Fin Based on the Fixed Fin Base Height (고정된 핀 바닥 높이에 기준한 비대칭 사다리꼴 핀의 최적화)

  • Song, Nyeon-Joo;Kang, Hyung-Suk
    • Journal of the Korean Society of Propulsion Engineers
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    • v.16 no.1
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    • pp.45-54
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    • 2012
  • Optimization of the asymmetric trapezoidal fin with various upper lateral surface slope is made using a two-dimensional analytic method. For the fixed fin base height, the optimum heat loss, fin length and effectiveness are represented as inner fluid convection characteristic number, fin base thickness, fin base height, fin shape factor and ambient convection characteristic number. For this optimum procedure, the optimum heat loss is defined as 95% of the maximum heat loss from the fin. One of the results shows that optimum heat loss and effectiveness seems independent of the fin shape factor while optimum fin length decreases almost linearly as the fin shape factor increases.

Heat Transfer from each surface for a 3-D Thermally Asymmetric Rectangular Fin

  • Kang, Hyung Suk
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.4 no.2
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    • pp.153-163
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    • 2000
  • The non-dimensional convective heat losses from each surface are investigated as a function of the non-dimensional fin length, width and the ratio of upper surface Biot number to bottom surface Biot number (Bi2/Bi1) using the three-dimensional separation of variables method. Heat loss ratio in view of each surface with the variation of Bi2/Bi1 is presented. The variation of the non-dimensioal temperare profile along the fin center line for a thermally asymmetric conditions is also presented.

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Comparison of Loss Function for Multi-Class Classification of Collision Events in Imbalanced Black-Box Video Data (불균형 블랙박스 동영상 데이터에서 충돌 상황의 다중 분류를 위한 손실 함수 비교)

  • Euisang Lee;Seokmin Han
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.24 no.1
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    • pp.49-54
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    • 2024
  • Data imbalance is a common issue encountered in classification problems, stemming from a significant disparity in the number of samples between classes within the dataset. Such data imbalance typically leads to problems in classification models, including overfitting, underfitting, and misinterpretation of performance metrics. Methods to address this issue include resampling, augmentation, regularization techniques, and adjustment of loss functions. In this paper, we focus on loss function adjustment, particularly comparing the performance of various configurations of loss functions (Cross Entropy, Balanced Cross Entropy, two settings of Focal Loss: 𝛼 = 1 and 𝛼 = Balanced, Asymmetric Loss) on Multi-Class black-box video data with imbalance issues. The comparison is conducted using the I3D, and R3D_18 models.

Bayes Estimation of Stress-Strength System Reliability under Asymmetric Loss Functions

  • Hong, Yeon-Woong
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.3
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    • pp.631-639
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    • 2003
  • Bayes estimates of reliability for the stress-strength system are obtained with respect to LINEX loss function. A reference prior distribution of the reliability is derived and Bayes estimates of the reliability are also obtained. These Bayes estimates are compared with corresponding estimates under squared-error loss function.

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A Study on Bayes and Empirical Bayes Estimates of Poisson Means under Asymmetric Loss Functions (비대칭 손실함수 아래서 포아송평균의 베이즈와 경험적베이즈 추정의 연구)

  • Youn Shik Chung;Chan Soo Kim
    • The Korean Journal of Applied Statistics
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    • v.7 no.2
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    • pp.131-143
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    • 1994
  • Under the asymmetric losses (entropy loss and Stein loss), we find the classes of Bayes and empiricla Bayes estimates for estimating the Poisson means when the distributin of means are believed a priori. Following the idea of Efron and Morris (1973), we have a computer simulation to compute a relative savings loss of proposed estimates as compared to the classical estimates.

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Development of Simple Bimodal Model for Charged Particle Coagulation (Bimodal 방법을 이용한 하전입자 응집 모델링)

  • Kim, Sang Bok;Song, Dong Keun;Hong, Won Seok;Shin, Wanho
    • Particle and aerosol research
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    • v.10 no.1
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    • pp.27-31
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    • 2014
  • A simple bimodal model has been developed to analyze charged particle coagulation by modifying previously suggested bimdal model for evolution of particle generation and growth. In the present model, two monodisperse modes are used and 40 charge nodes are assigned to each mode to account both change of the particle size and charge distribution. In addition, we also implemented the effect of electrostatic dispersion loss in the present model. Based on the developed model, we analyzed coagulation of asymmetric bipolar charged particles by computing evolutions of particle number concentration, geometric mean diameter of particles, charge asymmetric ratio and geometric standard deviation of particle size distribution for various initial charge asymmetric ratios. The number concentration of asymmetric bipolar charged particles decreases faster than that of neutral particles but that does not give faster growth of particles since the electrostatic dispersion loss overwhelms particle growth by coagulation.