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GlossaryMachine LearningDavies-Bouldin Index

Davies-Bouldin Index

[ˈdeɪviz ˈbuldɪn ˈɪndɛks]
Machine Learning
Last updated: December 9, 2024

Definition

A metric for evaluating clustering algorithms based on the average similarity between clusters.

Detailed Explanation

The Davies-Bouldin Index measures the average similarity between each cluster and its most similar cluster. Lower values indicate better clustering. It considers both the scatter within the clusters and the separation between clusters.

Use Cases

Used in market segmentation, pattern recognition, and data clustering validation.

Related Terms

Agglomerative Clustering

A hierarchical clustering approach that builds nested clusters by merging closer clusters.

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R-Squared

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Precision

The proportion of true positive predictions compared to all positive predictions made. Shows how many of the items identified as positive are actually positive.

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