Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Survival Tree01:19

Survival Tree

117
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
117
Reducing Line Loss01:18

Reducing Line Loss

174
In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss...
174
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

115
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
115
Line Loss01:10

Line Loss

273
The different configurations of source-load connections include wye (star) and delta connections. The relationship between line and phase voltages and currents varies depending on the configuration. When the source is supplying power, it is transmitted through the wires to the load, and during this transmission, some power is absorbed by the wires, leading to line loss.
Line loss impacts power delivery efficiency in a balanced three-phase circuit. The symmetry in such a circuit simplifies the...
273
Regression Toward the Mean01:52

Regression Toward the Mean

6.3K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.3K
Improving Translational Accuracy02:07

Improving Translational Accuracy

11.7K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
11.7K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Switchable Ultralong Chiral Signal Transmission and Gate Tunability in Organic Chiral Semiconductor.

Research (Washington, D.C.)·2026
Same author

Tirofiban for Reduction of TEAR: A Phase 2, Randomized, Open-Label, Blinded End Point, Controlled Trial.

Stroke·2026
Same author

Minimally invasive treatment of emphysematous pyelonephritis in diabetic patients: a comparative study.

BMC urology·2026
Same author

Site-specific biomechanical alterations of the knee during gait in ACL-deficient patients with concomitant cartilage lesions.

Frontiers in bioengineering and biotechnology·2026
Same author

Origin of Suppressed Photovoltage Loss in Organic Solar Cells With Additive Engineering.

Angewandte Chemie (International ed. in English)·2026
Same author

Neutrophil-lifecycle-inspired nanoplatform for the treatment of lung cancer bone metastasis.

Nanoscale·2026
Same journal

A robust ATUB-Net for bearing fault diagnosis under unbalanced sample scenarios.

ISA transactions·2026
Same journal

Data-driven trajectory tracking control of UAV systems under a novel probability-selection event-triggered mechanism.

ISA transactions·2026
Same journal

Predefined-time affine formation tracking control of unmanned surface vehicles with input saturation via adaptive fuzzy observers.

ISA transactions·2026
Same journal

Adaptive fault-tolerant safety-guaranteed fuzzy event-triggered rendezvous control for heterogeneous USV-UUV systems.

ISA transactions·2026
Same journal

Two-stage maximum likelihood weighted recursive least squares algorithm for nonlinear systems and an application in wind tunnel systems.

ISA transactions·2026
Same journal

Enhancing interpretable soft sensing with embedded hybrid modeling: the GraphTrans approach for industrial processes.

ISA transactions·2026
查看所有相关文章

相关实验视频

Updated: Jul 25, 2025

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
09:34

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

Published on: September 25, 2021

4.0K

线性指数式损失结合了对不平衡分类的深度学习.

Saiji Fu1, Duo Su2, Shilin Li3

  • 1School of Economics and Management, Beijing University of Posts and Telecommunications, No. 10 Xitucheng Road, Haidian District, Beijing, 100876, China.

ISA transactions
|June 29, 2023
PubMed
概括
此摘要是机器生成的。

本研究介绍了DLINEX,这是一种新的深度学习损失函数,旨在解决阶级不平衡问题. 在不平衡的数据集中,DLINEX有效地提高了少数群体类别的分类准确性.

关键词:
课堂不平衡学习学习分类 分类 分类 分类.深度学习是一种深度学习.在LINEX上出现损失.分段化 分段化 分段化 分段化

更多相关视频

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.9K
Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.1K

相关实验视频

Last Updated: Jul 25, 2025

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
09:34

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

Published on: September 25, 2021

4.0K
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.9K
Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.1K

科学领域:

  • 机器学习 机器学习
  • 计算机视觉 计算机视觉
  • 数据科学数据科学数据科学

背景情况:

  • 阶级不平衡是机器学习的一个持续挑战,经常导致少数阶级的表现不佳.
  • 传统方法在不平衡的数据中扎,将少数样本错误地归类为多数样本,这对现实世界有重大影响.

研究的目的:

  • 引入一个新的深度学习损失函数,DLINEX,以有效地处理类失衡问题.
  • 扩展线性指数 (LINEX) 损失函数用于多类不平衡的分类任务.

主要方法:

  • 该研究提出了DLINEX,这是LINEX损失函数的多类扩展,适用于深度学习.
  • DLINEX具有不对称的几何形状,允许通过单个参数对少数和难以分类的样本进行适应性聚焦.
  • 它同时通过考虑实例属性来优化类间和类内部的多样性.

主要成果:

  • 在CIFAR-10 (不平衡比率200) 上,DLINEX获得了42.08%的G-平均值,在HAM10000上获得了79.06%的G-平均值,在DRIVE,CHASEDB1和STARE数据集上获得了高的F1得分.
  • 实验证明了DLINEX在图像级和像素级不平衡分类任务中的卓越性能.

结论:

  • 在深度学习中,DLINEX为阶级不平衡提供了有效的解决方案.
  • 拟议的损失函数在识别不同数据集中的少数和具有挑战性的样本方面取得了显著的改进.