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

Bar Graph01:07

Bar Graph

16.7K
A bar graph is also called a bar chart and consists of bars that are separated from each other. It either uses horizontal or vertical bars to show comparisons among categories. The bars can be rectangles, or they can be rectangular boxes (used in three-dimensional plots). One axis of the graph represents the specific categories being compared, and the other axis shows a discrete value. In this graph, the length of the bar for each category is proportional to the number or percent of individuals...
16.7K
Multiple Bar Graph01:07

Multiple Bar Graph

5.3K
As the name suggests, a multiple bar graph is the same as a bar graph but has multiple bars to depict relationships between different data values. One can include as many parameters as possible. However, each parameter must have the same unit of measurement.
Each bar or column in the multiple bar graph represents a data value. These graphs are used primarily in interrelating two or more sets of data. The categories of different kinds of data are listed along the horizontal or x-axis, whereas...
5.3K
Ogive Graph01:07

Ogive Graph

5.7K
An ogive graph is sometimes called a cumulative frequency polygon. It is one type of frequency polygon that shows cumulative frequency. In other words, the cumulative percentages are added to the graph from left to right. An ogive graph plots cumulative frequency on the vertical y-axis and class boundaries along the horizontal x-axis. It’s very similar to a histogram; only instead of rectangles, an ogive displays a single point where the top right of the rectangle would be. Creating this...
5.7K
Time-Series Graph00:54

Time-Series Graph

4.4K
A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct a time-series graph, one must look at both pieces of a paired data set. The horizontal axis is used to plot the time increments, and the vertical axis is used to plot the values of the variable that one is measuring. By using the axes in this way, each point on the graph will correspond to time and a measured quantity. The points on the graph...
4.4K
Cluster Sampling Method01:20

Cluster Sampling Method

12.0K
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...
12.0K
Contingency Table01:29

Contingency Table

2.5K
A contingency table provides a way of portraying data that can facilitate calculating probabilities. It is a method of displaying a frequency distribution as a table with rows and columns to show how two variables may be dependent (contingent) upon each other; The table helps determine conditional probabilities quite quickly and can help systematically organize, analyze and quantify data. The table displays sample values concerning two variables that may be dependent or contingent on one...
2.5K

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

EyeRAG: graph retrieval-augmented generation for safe and accurate clinical dialogue in ophthalmology.

NPJ digital medicine·2026
Same author

Efficacy and safety of doravirine/lamivudine/tenofovir as initial treatment for people living with HIV in China.

Antimicrobial agents and chemotherapy·2026
Same author

Rational Dual-Site Doping of the Hematite Photoanode Unlocks Efficient Solar Water Splitting.

ACS applied materials & interfaces·2026
Same author

Task-oriented visual SLAM: a comprehensive map classification framework for dynamic indoor robot manipulation.

Scientific reports·2026
Same author

The safety and tolerability of oral TDF/FTC as pre-exposure prophylaxis among men who have sex with men in China: a prospective cohort study.

BMC infectious diseases·2026
Same author

Relationship between time management disposition and academic procrastination among Chinese students: Systematic review and meta analysis.

Acta psychologica·2026

相关实验视频

Updated: Jul 25, 2025

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

7.0K

简单的对比图集群简单的对比图集群

Yue Liu, Xihong Yang, Sihang Zhou

    IEEE transactions on neural networks and learning systems
    |June 27, 2023
    PubMed
    概括
    此摘要是机器生成的。

    本研究介绍了一种简单的对比图集群 (SCGC) 算法,可以提高效率和性能. 与现有方法相比,SCGC在深度图形集群中取得了卓越的结果,速度明显提升.

    更多相关视频

    A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'
    10:31

    A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'

    Published on: February 10, 2017

    11.1K
    ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
    05:12

    ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

    Published on: January 16, 2019

    11.5K

    相关实验视频

    Last Updated: Jul 25, 2025

    Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
    12:27

    Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

    Published on: February 15, 2017

    7.0K
    A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'
    10:31

    A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'

    Published on: February 10, 2017

    11.1K
    ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
    05:12

    ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

    Published on: January 16, 2019

    11.5K

    科学领域:

    • 图形神经网络 图形神经网络
    • 机器学习 机器学习
    • 数据挖掘 数据挖掘

    背景情况:

    • 对比式学习在深度图形集群中显示出前景.
    • 现有的方法受到低效的数据增强和图形卷积运算的影响.

    研究的目的:

    • 提出一个简单的对比图集群 (SCGC) 算法.
    • 为了提高深度图表集群的效率和性能.

    主要方法:

    • 引入了简化的网络架构,包括预处理和两层多层感知器 (MLP) 骨干.
    • 开发了一种新的数据增强策略,通过直接使用参数未共享的语编码器来扰乱节点嵌入.
    • 设计了一个跨视图结构一致性目标函数,以增强区分能力.

    主要成果:

    • 在七个基准数据集中,SCGC展示了有效性和优越性.
    • 与最近的深度集群竞争对手相比,实现了至少7倍的平均速度.
    • 通过广泛的实验结果来验证.

    结论:

    • SCGC提供了一种高效有效的方法来进行深度图表集群.
    • 为架构,数据增强和目标函数提出的方法显著提高了性能和速度.
    • SCGC代表了在图表表示学习集群领域的显著进步.