Entropy Weight Method
Version 1.0.0 · Updated 2026-07-30
CORE DEFINITION
Utilizes the principle of information entropy to determine indicator weights: the smaller the information entropy (i.e., the more dispersed the data), the stronger the indicator's discriminative ability, and the higher its weight.
SCAFFOLDING EFFECT
Reduce cognitive load
Let the data speak, objectively assign weights. Avoid biases from subjective weight setting, and use the degree of variation in the data itself to determine importance. (Merged: Entropy Weight Method, Entropy Evaluation Method)
Anchor fast decisions
In multi-indicator evaluation, the weights are determined by the dispersion degree (entropy) of each indicator's data itself: indicators with smaller information entropy (greater differences) receive larger weights. This is an objective weighting method.
MINIMUM ACTION
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Source support: Explicit
- zh.wikipedia.orghttps://zh.wikipedia.org/wiki/%E7%86%B5%E6%9D%83%E6%B3%95verified
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