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mutual information是什麼意思,mutual information的意思翻譯、用法、同義詞、例句

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  • [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數約束的優化得分函數。

  • Normalized mutual information was adopted as the similarity measure.

    使用歸一化互信息作為相似性量度。

  • This paper proposed a mutual information based method for generating videoion.

    提出了一種基于交互信息量的視頻摘要生成方法。

  • Teaching is not simply teaching and learning, but a mutual information exchange.

    教學不是我教你學,而是兩主體之間的雙向信息互換。

  • The new image multi-threshold method based on fuzzy mutual information is proposed.

    提出了多阈值模糊互信息圖像分割新方法。

  • 網絡擴展資料

    互信息(Mutual Information) 是信息論中用于衡量兩個隨機變量之間相互依賴性的指标。它量化了通過觀察一個變量能獲得的關于另一個變量的信息量。以下是詳細解釋:


    1.基本定義


    2.數學公式

    互信息有兩種常見表達形式:
    ① 基于熵的表達式:
    $$ I(X; Y) = H(X) - H(X|Y) = H(Y) - H(Y|X) $$
    其中,

    ② 基于概率分布的表達式:
    $$ I(X; Y) = sum{x in X} sum{y in Y} p(x, y) log frac{p(x, y)}{p(x)p(y)} $$


    3.關鍵性質


    4.應用場景


    5.示例

    假設有兩個二值變量$X$和$Y$:


    互信息是一種強大的統計工具,廣泛用于量化變量間任意形式的依賴性,尤其適用于複雜系統分析和機器學習模型優化。其單位通常為比特(bit,底數為2時)或納特(nat,底數為$e$時)。

    網絡擴展資料二

    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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