mutualinformation

Mutual Information (互信息)

Mutual information is a concept from information theory that measures the amount of information that one random variable contains about another random variable.

互信息是信息论中的一个概念，用来衡量一个随机变量关于另一个随机变量包含的信息量。

词语辨析

“Mutual information”一般用作名词，表示两个随机变量之间的信息共享程度。这个词没有明显的形容词形式。

词汇扩充

• Information theory: 信息论

• Random variable: 随机变量

• Entropy: 熵

• Joint distribution: 联合分布

近义词

• Shared information: 共享信息

• Conditional entropy: 条件熵

反义词

• Independent variables: 独立变量

词典引用

Collins Dictionary: Mutual information is a measure of the amount of information that one random variable contains about another.

牛津词典: Mutual information quantifies the amount of information obtained about one random variable through the other random variable.

例句

• The concept of mutual information is crucial in statistics.

  互信息的概念在统计学中至关重要。

• We can calculate the mutual information between two datasets to determine their relationship.

  我们可以计算两个数据集之间的互信息以确定它们的关系。

• Maximizing mutual information can lead to better model performance.

  最大化互信息可以提高模型性能。

• The mutual information score indicates how much knowing one variable reduces uncertainty about another.

  互信息得分表明了解一个变量在多大程度上减少了对另一个变量的不确定性。

• In machine learning, mutual information is often used for feature selection.

  在机器学习中，互信息通常用于特征选择。

• Understanding mutual information helps in designing efficient algorithms.

  理解互信息有助于设计高效的算法。

• The mutual information between two signals can reveal hidden patterns.

  两个信号之间的互信息可以揭示隐藏模式。

• Researchers applied mutual information to analyze the correlation between variables.

  研究人员应用互信息分析变量之间的相关性。

• To improve accuracy, the model incorporates mutual information into its calculations.

  为了提高准确性，该模型将互信息纳入其计算中。

• Using mutual information, we can assess the dependency between features.

  通过使用互信息，我们可以评估特征之间的依赖关系。

• Graphical models often utilize mutual information to represent dependencies.

  图形模型通常利用互信息来表示依赖关系。

• The mutual information metric is advantageous in many applications.

  互信息指标在许多应用中都具有优势。

• In data mining, mutual information can help identify interesting patterns.

  在数据挖掘中，互信息可以帮助识别有趣的模式。

• By analyzing mutual information, we can derive insights from our data.

  通过分析互信息，我们可以从数据中得出见解。

• Calculating mutual information requires understanding probability distributions.

  计算互信息需要了解概率分布。

• The mutual information approach is widely accepted in the field of information theory.

  互信息方法在信息论领域被广泛接受。

• Exploring mutual information provides a deeper understanding of variable interactions.

  探索互信息可以更深入地理解变量之间的相互作用。

• Applications of mutual information span various scientific disciplines.

  互信息的应用跨越了多个科学学科。

• By leveraging mutual information, we can enhance predictive models.

  通过利用互信息，我们可以增强预测模型。