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Small corrections in docs validate.md #271

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merged 5 commits into from
Apr 14, 2024
Merged

Small corrections in docs validate.md #271

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92b1384
links in validate.md
jaksle Jan 23, 2024
aa534b5
remove nclusters
jaksle Jan 23, 2024
cc6e252
Revert "remove nclusters"
alyst Apr 14, 2024
42e68e1
validate: reuse clu_quality_data
alyst Apr 14, 2024
567b0b8
validate: tweak plot layout, SVG
alyst Apr 14, 2024
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16 changes: 8 additions & 8 deletions docs/source/validate.md
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Original file line number Diff line number Diff line change
Expand Up @@ -85,7 +85,7 @@ mutualinfo

## Clustering quality indices

[`clustering_quality()`][@ref clustering_quality] methods allow computing *intrinsic* clustering quality indices,
[`clustering_quality()`](@ref clustering_quality) methods allow computing *intrinsic* clustering quality indices,
i.e. the metrics that depend only on the clustering itself and do not use the external knowledge.
These metrics can be used to compare different clustering algorithms or choose the optimal number of clusters.

Expand Down Expand Up @@ -180,7 +180,7 @@ Higher values indicate better separation of clusters w.r.t. point distances.
silhouettes
```

[`clustering_quality(..., quality_index=:silhouettes)`][@ref clustering_quality]
[`clustering_quality(..., quality_index=:silhouettes)`](@ref clustering_quality)
provides mean silhouette metric for the datapoints. Higher values indicate better quality.

## References
Expand Down Expand Up @@ -214,11 +214,11 @@ X = hcat([4., 5.] .+ 0.4 * randn(2, 10),
[9., -5.] .+ 0.4 * randn(2, 5),
[-4., -9.] .+ 1 * randn(2, 5))

nclusters = 2:5
clusterings = kmeans.(Ref(X), nclusters)
№_clu = 2:5
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I think "№" symbol typically denotes "sequential number", e.g. "cluster №3", but not the quantity of items.

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I am no expert here, I always thought it is just old abbreviation for "number" with no further nuance. We can change to n_clu or something similar.

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I reverted it back to nclusters

clusterings = kmeans.(Ref(X), №_clu)

plot((
plot(nclusters,
plot(№_clu,
clustering_quality.(Ref(X), clusterings, quality_index = qidx),
marker = :circle,
title = ":$qidx", label = nothing,
Expand All @@ -237,11 +237,11 @@ X = hcat([4., 5.] .+ 0.4 * randn(2, 10),
[-4., -9.] .+ 1 * randn(2, 5))

fuzziness = 2
fuzzy_nclusters = 2:5
fuzzy_clusterings = fuzzy_cmeans.(Ref(X), fuzzy_nclusters, fuzziness)
fuzzy_№_clu = 2:5
fuzzy_clusterings = fuzzy_cmeans.(Ref(X), fuzzy_№_clu, fuzziness)

plot((
plot(fuzzy_nclusters,
plot(fuzzy_№_clu,
clustering_quality.(Ref(X), fuzzy_clusterings,
fuzziness = fuzziness, quality_index = qidx),
marker = :circle,
Expand Down
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