mutual information是什么意思，mutual information的意思翻译、用法、同义词、例句
常用词典
[自] 交互信息
例句
A score function for optimization based on maximum mutual information entropy with odditional restriction is proposed.
提出了基于最大互信息熵且具有奇数约束的优化得分函数。
Normalized mutual information was adopted as the similarity measure.
使用归一化互信息作为相似性量度。
This paper proposed a mutual information based method for generating videoion.
提出了一种基于交互信息量的视频摘要生成方法。
Teaching is not simply teaching and learning, but a mutual information exchange.
教学不是我教你学，而是两主体之间的双向信息互换。
The new image multi-threshold method based on fuzzy mutual information is proposed.
提出了多阈值模糊互信息图像分割新方法。
网络扩展资料
Mutual information（互信息）is a statistical measure used to quantify the amount of information shared by two variables. It is often used in machine learning and natural language processing to evaluate the relationship between two sets of data.
Mutual information measures the degree of dependence between two variables by calculating the amount of information that one variable provides about the other. This is done by comparing the joint probability distribution of the two variables to the product of their marginal probability distributions.
For example, if we have two variables A and B, mutual information can be calculated as follows:
MI(A,B) = sum( P(A,B) * log( P(A,B) / (P(A) * P(B)) ) )where P(A,B) is the joint probability distribution of A and B, and P(A) and P(B) are their marginal probability distributions.
In natural language processing, mutual information can be used to identify the degree of association between two words or phrases. For example, the mutual information between the words "cat" and "mouse" is likely to be higher than the mutual information between "cat" and "computer," because the former pair is more commonly associated with each other.
Some synonyms for mutual information include joint entropy and co-information. Antonyms could include independence or unrelatedness.
In summary, mutual information is a statistical measure that calculates the amount of information shared by two variables. It is commonly used in machine learning and natural language processing to evaluate the relationship between two sets of data.
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