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Correction of a formula for silhouette coefficient 

Source:
http://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html
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kaksat 2018-08-06 20:21:35 +02:00
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commit 50aeba2e67
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08_dimensionality_reduction.ipynb
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@ -2606,7 +2606,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"Another approach is to look at the _silhouette score_, which is the mean _silhouette coefficient_ over all the instances. An instance's silhouette coefficient is equal to $(a - b)/\\max(a, b)$ where $a$ is the mean distance to the other instances in the same cluster (it is the _mean intra-cluster distance_), and $b$ is the _mean nearest-cluster distance_, that is the mean distance to the instances of the next closest cluster (defined as the one that minimizes $b$, excluding the instance's own cluster). The silhouette coefficient can vary between -1 and +1: a coefficient close to +1 means that the instance is well inside its own cluster and far from other clusters, while a coefficient close to 0 means that it is close to a cluster boundary, and finally a coefficient close to -1 means that the instance may have been assigned to the wrong cluster."
"Another approach is to look at the _silhouette score_, which is the mean _silhouette coefficient_ over all the instances. An instance's silhouette coefficient is equal to $(b - a)/\\max(a, b)$ where $a$ is the mean distance to the other instances in the same cluster (it is the _mean intra-cluster distance_), and $b$ is the _mean nearest-cluster distance_, that is the mean distance to the instances of the next closest cluster (defined as the one that minimizes $b$, excluding the instance's own cluster). The silhouette coefficient can vary between -1 and +1: a coefficient close to +1 means that the instance is well inside its own cluster and far from other clusters, while a coefficient close to 0 means that it is close to a cluster boundary, and finally a coefficient close to -1 means that the instance may have been assigned to the wrong cluster."
]
},
{