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

Correlations02:20

Correlations

33.2K
Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
33.2K
Classification of Signals01:30

Classification of Signals

532
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
532
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

129
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
129
Correlation01:09

Correlation

11.8K
In statistics, two variables are said to be correlated if the values of one variable are associated with the other variable. Depending on the relationship between two variables, correlation can be of three types– positive correlation, negative correlation, and zero correlation.
Two variables, for example, a and b, are said to be positively correlated if both variables move in the same direction. In other words, a positive correlation exists between two variables, a and b, if:
11.8K
Labeling Emotion01:20

Labeling Emotion

178
Emotional labeling is a cognitive process that involves identifying and naming one's emotions, such as anger, fear, happiness, or sadness. It allows individuals to recognize and express their internal emotional states, a critical aspect of emotional regulation and communication. Labeling emotions requires more than mere recognition; it also involves drawing upon memory and contextual cues to understand the current situation and apply a corresponding emotional label. For instance, feeling...
178
Correlation and Regression00:53

Correlation and Regression

1.3K
In statistics, correlation describes the degree of association between two variables. In the subfield of linear regression, correlation is mathematically expressed by the correlation coefficient, which describes the strength and direction of the relationship between two variables. The coefficient is symbolically represented by 'r' and ranges from -1 to +1. A positive value indicates a positive correlation where the two variables move in the same direction. A negative value suggests a...
1.3K

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

Discovery of Novel Small-Molecule Inhibitors of PD-1/PD-L1 Interaction via Structural Simplification Strategy.

Molecules (Basel, Switzerland)·2021
Same author

Case Report: Pink Urine Syndrome Following Exposure to Propofol: A Rare, Impressive but Benign Complication.

Frontiers in pharmacology·2021
Same author

TMT-based quantitative proteomic analysis of the effects of Pseudomonas syringae pv. tabaci (Pst) infection on photosynthetic function and the response of the MAPK signaling pathway in tobacco leaves.

Plant physiology and biochemistry : PPB·2021
Same author

Peritumoral Microgel Reservoir for Long-Term Light-Controlled Triple-Synergistic Treatment of Osteosarcoma with Single Ultra-Low Dose.

Small (Weinheim an der Bergstrasse, Germany)·2021
Same author

Pseudolaric acid B ameliorates synovial inflammation and vessel formation by stabilizing PPARγ to inhibit NF-κB signalling pathway.

Journal of cellular and molecular medicine·2021
Same author

PSSP-MVIRT: peptide secondary structure prediction based on a multi-view deep learning architecture.

Briefings in bioinformatics·2021

相关实验视频

Updated: Jul 21, 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

7.6K

在线多标签流媒体基于标签组相关性和特征交互的特征选择.

Jinghua Liu1,2,3, Songwei Yang1,2,3, Hongbo Zhang1,2,3

  • 1Department of Computer Science and Technology, Huaqiao University, Xiamen 361021, China.

Entropy (Basel, Switzerland)
|July 29, 2023
PubMed
概括

本研究引入了一种新的在线流媒体功能选择方法 (OSLGC),该方法考虑了标签组相关性和功能相互作用. 该方法在动态数据场景中增强了预测性能和稳定性.

关键词:
标签组相关性 标签组相关性多标签特征选择多标签特征选择这是相互信息的互惠.流媒体功能提供流媒体功能.

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

802
Cross-Modal Multivariate Pattern Analysis
13:51

Cross-Modal Multivariate Pattern Analysis

Published on: November 9, 2011

20.0K

相关实验视频

Last Updated: Jul 21, 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

7.6K
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

802
Cross-Modal Multivariate Pattern Analysis
13:51

Cross-Modal Multivariate Pattern Analysis

Published on: November 9, 2011

20.0K

科学领域:

  • 机器学习 机器学习
  • 数据挖掘 数据挖掘
  • 人工智能的人工智能

背景情况:

  • 多标签功能选择对于动态数据采集至关重要.
  • 现有的方法往往过于简化标签关系或忽略特征交互.
  • 现实数据呈现出复杂的标签相关性和特定的特征-标签依赖性.

研究的目的:

  • 开发一种新的在线流媒体功能选择方法 (OSLGC).
  • 解决在动态环境中处理标签相关性和特征交互方面的局限性.
  • 为了提高数据流中的特征选择的准确性和稳定性.

主要方法:

  • 利用图形理论对相关标签进行分组.
  • 整合标签权重和相互信息以量化特征-标签关系.
  • 实施一个移动窗口框架,用于在线功能相关性和交互分析.

主要成果:

  • 与现有的多标签特征选择算法相比,提出的OSLGC方法表现出更高的性能.
  • 实验显示,预测性能,统计分析和稳定性显著改善.
  • 废弃性研究验证了拟议成分的有效性.

结论:

  • 在流数据中,OSLGC有效地处理标签组相关性和特征交互.
  • 该方法为动态特征选择场景提供了强大的解决方案.
  • 这些发现表明OSLGC是多标签流媒体功能选择的有希望的进步.