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Cluster Iris Flowers

Guided clustering project · 20 steps · K-means clustering

About

Learn unsupervised learning by grouping Iris flowers and checking how the discovered clusters compare to known species.

Data

Loaded from scikit-learn via load_iris. Four flower measurements with three species labels for reference.

Task

Complete TODOs in order, run KMeans, pick a good k with elbow and silhouette, then evaluate cluster quality with ARI.

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Cell 1

Step 1: Imports

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Step 2: Load dataset

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Step 3: Build DataFrame

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Step 4: Add species names

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Step 5: Shape and class counts

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Step 6: Preview rows

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Step 7: Quick summary stats

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Step 8: 2D scatter by true species

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Step 9: Prepare feature matrix

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Step 10: Scale features

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Step 11: KMeans with k=3

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Step 12: Cluster sizes

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Step 13: Compare cluster vs species

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Step 14: Clusters in petal space

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Step 15: Inertia for k=1..8

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Step 16: Elbow plot

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Step 17: Silhouette for k=2..8

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Step 18: Silhouette plot

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Step 19: Evaluate clustering quality

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Step 20: Inspect cluster centers