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相关概念视频

Time-Series Graph00:54

Time-Series Graph

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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...
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Quantifying and Rejecting Outliers: The Grubbs Test01:02

Quantifying and Rejecting Outliers: The Grubbs Test

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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...
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Construction of Frequency Distribution01:15

Construction of Frequency Distribution

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A frequency distribution table can be constructed using the steps given below.
First, make a table with two columns—one with the title of the data that needs to be organized, and the other column for frequency. [Draw a third column for tally marks if needed]. Then, take a look at the items given in the data set and decide if an ungrouped frequency distribution table or a grouped frequency distribution table would be more suitable. If there are large sets of different values, then it is...
7.7K
Probability Histograms01:17

Probability Histograms

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A probability histogram is a visual representation of a probability distribution. Similar a typical histogram, the probability histogram consists of contiguous (adjoining) boxes. It has both a horizontal axis and a vertical axis. The horizontal axis is labeled with what the data represents. The vertical axis is labeled with probability. Each rectangular bar in the histogram is 1 unit wide, which suggests that the area under each bar equals the probability, P(x), where x is 1, 2, 3, and so on.
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Multiple Bar Graph01:07

Multiple Bar Graph

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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...
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Expected Frequencies in Goodness-of-Fit Tests01:19

Expected Frequencies in Goodness-of-Fit Tests

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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).
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Updated: Jul 4, 2025

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
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在图表中计算频繁模式的支持措施的概括设计.

Jinghan Meng1, Napath Pitaksirianan1, Yicheng Tu1

  • 1Dept. of Computer Science, University of South Florida, Tampa, Florida, USA.

Proceedings : ... IEEE International Conference on Big Data. IEEE International Conference on Big Data
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PubMed
概括
此摘要是机器生成的。

本研究介绍了为创建新的频次次段采矿 (FSM) 支持措施的一般条件. 这些条件概括了现有的测量方法,并引入了新的测量方法,弥合了计算差距.

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科学领域:

  • 计算机科学 计算机科学
  • 图形理论 图形理论
  • 数据挖掘 数据挖掘

背景情况:

  • 频繁的子图挖掘 (FSM) 在数据分析中至关重要.
  • 开发有效的FSM模式支持措施是一个关键的挑战.
  • 当前的方法经常使用超图框架,统一重叠图 (MIS) 和最小图像/实例 (MNI) 措施.

研究的目的:

  • 探索现有的FSM支持措施类型之间的空间.
  • 在超图框架内为设计新的FSM支持措施提供足够的一般条件.
  • 引导开发新的,高效的,用户定义的支持措施.

主要方法:

  • 开发了在超图框架中构建支持措施的一般足够条件.
  • 应用这些条件来概括现有的措施,如最小图像/实例 (MNI) 和最小实例 (MI).
  • 引入了一种新的最大独立下边界集 (MISS) 测量方法.

主要成果:

  • 提出的条件成功地将MNI和MI的测量概括起来,使用户定义的线性时间测量成为可能.
  • 在计算复杂性和支持数量方面,新的最大独立子边界集 (MISS) 测量有效地弥合了MIS和MI测量之间的差距.
  • 已证明适用于超出重叠图框架的措施.

结论:

  • 建立的充分条件为创建新的FSM支持措施提供了坚实的框架.
  • 这些通用和新的措施提高了频繁的子图采矿的灵活性和效率.
  • 在FSM中,MISS测量为平衡计算成本和模式频率提供了一个有价值的新选择.