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

Sampling Plans01:23

Sampling Plans

169
Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
169
Cluster Sampling Method01:20

Cluster Sampling Method

11.6K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
11.6K
Quantifying and Rejecting Outliers: The Grubbs Test01:02

Quantifying and Rejecting Outliers: The Grubbs Test

1.5K
Sometimes, a data set can have a recorded numerical observation that greatly  deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier.  To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This...
1.5K
Frequency-dependent Selection01:21

Frequency-dependent Selection

21.9K
When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.
21.9K
Wilcoxon Signed-Ranks Test for Matched Pairs01:09

Wilcoxon Signed-Ranks Test for Matched Pairs

88
The Wilcoxon signed-rank test for matched pairs evaluates the null hypothesis by combining the ranks of differences with their signs. It essentially tests whether the median of the differences in a population of matched pairs is zero. Since the test incorporates more information than the sign test, it generally yields more trustable conclusions. This test also does not require the data to follow a normal distribution, but two conditions must be met for it to be applicable: (1) the data must...
88
Random Sampling Method01:09

Random Sampling Method

11.0K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
11.0K

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

Visualizing dual-sites synergistic catalysis in non-iridium catalysts for acidic oxygen evolution reaction.

Nature communications·2026
Same author

Valsartan Reduces Myocardial Ischemia-Reperfusion Injury by Inhibiting Ferritinophagy-Mediated Ferroptosis.

Journal of cellular and molecular medicine·2026
Same author

Hypericin Suppresses Liver Cancer Through Autophagic Degradation of AKT and Eliciting Antitumor Immune Response.

Cancer science·2026
Same author

Immunomodulatory effects of Yang He decoction on cyclophosphamide-induced immunosuppression in mice: restoration of immune organ integrity and cytokine balance.

Frontiers in pharmacology·2026
Same author

Functional Suppression of SCAP Triggers Endoplasmic Reticulum Stress-Dependent Ferroptosis by Impairing Cholesterol Metabolism in Gastric Cancer.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Effects of Hydrogen-Rich Water on Juvenile Largemouth Bass (<i>Micropterus salmoides</i>) Under Acute Low-Temperature Stress.

Antioxidants (Basel, Switzerland)·2026

相关实验视频

Updated: Jun 9, 2025

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.4K

在噪音强大的深度度度度学习中提高样本利用率,使用基于子组的正对选择.

Zhipeng Yu, Qianqian Xu, Yangbangyan Jiang

    IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
    |October 22, 2024
    PubMed
    概括

    本研究引入了基于子组的正对选择 (SGPS) 框架,以改善使用噪音标签的深度度度度学习 (DML). SGPS通过为杂数据创建可靠的正对来提高样本利用率,优于现有方法.

    科学领域:

    • 人工智能的人工智能
    • 机器学习 机器学习
    • 计算机视觉 计算机视觉

    背景情况:

    • 现实数据中的噪音标签会降低深度学习模型的性能.
    • 对噪音标签的稳定性在分类中得到了很好的研究,但在深度度度度学习 (DML) 中未得到充分探索.
    • 目前用于噪音标签的DML方法经常丢弃潜在的有用数据,减少样本利用率.

    研究的目的:

    • 提出一个新的噪声强大的DML框架,以子组为基础的正对选择 (SGPS).
    • 通过在DML中构建可靠的正对来提高样本利用率.
    • 为了提高DML模型在标签噪声存在时的性能.

    主要方法:

    • SGPS采用基于概率的策略来识别干净和杂的样本.
    • 一个子组生成模块在子组内发现类似的样本,用于噪音数据.
    • 积极的原型从类似的样本中聚合起来,并应用了量身定制的对比损失.
    • 该框架很容易与现有的对智能DML任务集成.

    主要成果:

    • SGPS有效地识别了干净和杂的样品.
    • 它为杂的样本构建了信息化的积极原型,提高了它们的实用性.

    更多相关视频

    Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
    03:37

    Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

    Published on: March 1, 2024

    645
    A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
    08:12

    A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

    Published on: March 1, 2022

    2.4K

    相关实验视频

    Last Updated: Jun 9, 2025

    Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
    07:35

    Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

    Published on: October 11, 2018

    7.4K
    Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
    03:37

    Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

    Published on: March 1, 2024

    645
    A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
    08:12

    A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

    Published on: March 1, 2022

    2.4K
  • 在合成和现实世界数据集上的实验证明了SGPS的有效性.
  • 拟议的方法优于最先进的噪音标签DML技术.
  • 结论:

    • SGPS提供了一个强大的和有效的解决方案,用于深度度度度学习与杂的标签.
    • 与现有方法相比,该框架显著提高了样本利用率.
    • SGPS为强大的机器学习领域提供了宝贵的贡献.