From 4d53fa14ee0cd615444aca6f6ba176e0ccc1b5be Mon Sep 17 00:00:00 2001
From: TheSiahxyz <164138827+TheSiahxyz@users.noreply.github.com>
Date: Mon, 29 Apr 2024 22:06:12 -0400
Subject: init

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+---
+id: NMI
+aliases:
+  - Normalized mutual information (NMI)
+tags: []
+---
+
+## Normalized mutual information (NMI)
+
+- Mutual information:
+  - Quantifies the amount of shared info between $I(C,T) =
+    \sum_{i=1}^{r}\sum{j=1}^{k}p_{ij}log\dfrac{p{ij}}{p_{c_i}p_{T_j}}$
+  - Measures the dependency between the observed joint probability $p_{ij}$ of
+    $C$ and $T$, and the expected joint probability $p_{Ci} * p_P{Tj}$ under the
+    independence assumption
+  - When $C$ and $T$ are independent, $p_{ij} = p_{Ci} * p_{Tj}, I(C, T) = 0$.
+    However, there is no upper bound on the mutual information
+- **Normalized mutual information (NMI)** $$N M I(C, T) =
+  \sqrt{\dfrac{I(C,T)}{H(C)}*\dfrac{I(C, T)}{H(T)}} = \dfrac{I(C,
+  T)}{\sqrt{H(C) * H(T)}}$$
+  - Value range of NMI: [0, 1]. Value close to 1 indicates a good clustering
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