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

Aggregates Classification01:29

Aggregates Classification

970
Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
970
Quantifying and Rejecting Outliers: The Grubbs Test01:02

Quantifying and Rejecting Outliers: The Grubbs Test

3.5K
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...
3.5K
Gaussian Elimination: Problem Solving01:30

Gaussian Elimination: Problem Solving

162
Systems of linear equations in several variables are pivotal in modeling complex scenarios involving multiple unknowns and constraints. Such systems are widely used in various fields to represent relationships where several conditions must be simultaneously satisfied. Each variable in the system corresponds to an unknown quantity, while each equation imposes a linear constraint, leading to a structured approach for analyzing and solving real-world problems.A system of three equations with three...
162
Improving Translational Accuracy02:07

Improving Translational Accuracy

14.1K
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...
14.1K
Improving Translational Accuracy02:07

Improving Translational Accuracy

3.5K
3.5K
Expected Frequencies in Goodness-of-Fit Tests01:19

Expected Frequencies in Goodness-of-Fit Tests

7.2K
A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n)  to the number of categories (k).
7.2K

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

NOTCH2NLC Intermediate-Length Repeat Expansions Are Associated with Parkinson Disease.

Annals of neurology·2020
Same author

AUTOPHAGY-RELATED14 and Its Associated Phosphatidylinositol 3-Kinase Complex Promote Autophagy in Arabidopsis.

The Plant cell·2020
Same author

Myocardial injury and risk factors for mortality in patients with COVID-19 pneumonia.

International journal of cardiology·2020
Same author

IDOL gene variant is associated with hyperlipidemia in Han population in Xinjiang, China.

Scientific reports·2020
Same author

LncRNA-5657 silencing alleviates sepsis-induced lung injury by suppressing the expression of spinster homology protein 2.

International immunopharmacology·2020
Same author

Hybrid Hydrogels for Synergistic Periodontal Antibacterial Treatment with Sustained Drug Release and NIR-Responsive Photothermal Effect.

International journal of nanomedicine·2020

相关实验视频

Updated: Jan 17, 2026

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

7.9K

通过基于坐标的少数特征采矿来改进高斯的天真贝叶斯对不平衡数据的分类.

Wei Wang1, Li Yan1, Fen Liu1

  • 1School of Business, Guilin Tourism University, Guilin, Guangxi, China.

PeerJ. Computer science
|September 24, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的坐标转换算法,以提高高斯天真贝叶斯 (GNB) 对不平衡数据的分类性能. 辐射局部相对密度变化 (RLDC) 方法增强了少数阶级的代表性,而不改变数据分布,优于传统的采样技术.

关键词:
协调转换的转换.高斯的天真贝叶斯分类器.不平衡的数据不平衡的数据少数阶级的突出特征 少数阶级的突出特征

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

1.2K

相关实验视频

Last Updated: Jan 17, 2026

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

7.9K
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

1.2K

科学领域:

  • 机器学习 机器学习
  • 数据科学数据科学数据科学
  • 人工智能的人工智能

背景情况:

  • 斯天真贝叶斯 (GNB) 分类器在不平衡的数据集中扎,导致性能下降.
  • 现有的数据不平衡的采样技术会改变数据分布,并可能导致过度匹配或类重叠.
  • 需要方法来改善GNB在不平衡数据上的表现,而无需修改原始数据集.

研究的目的:

  • 提出一种基于辐射局部相对密度变化 (RLDC) 的新型坐标转换算法.
  • 通过生成新的功能,提高GNB对不平衡数据集的分类性能.
  • 为了保持原始数据的数量和分布,同时改善少数阶级的代表性.

主要方法:

  • 开发了一个坐标转换算法,将绝对坐标转换为RLDC相对坐标.
  • RLDC转换揭示了潜在的局部相对密度变化特征,突出了少数阶级的模式.
  • 将转换的特征应用于GNB分类器,以改进少数群体类概率估计.

主要成果:

  • 基于RLDC的坐标转换算法显著改善了GNB在20个不平衡数据集上的性能.
  • 该算法在三个分类评估指标中表现优于14个传统的抽样算法.
  • 与现有方法相比,实现了21.84%,33.45%和54.63%的平均性能改善.

结论:

  • RLDC坐标转换提供了一种新且有效的方法来处理GNB分类中的不平衡数据.
  • 这种方法通过在不改变原始数据的情况下创建信息特征来提高分类准确性.
  • 该算法在不平衡的分类问题上展示了重要的理论和实践价值.