How do I evaluate the results of dimension reduction techniques?
You can evaluate dimension reduction results by examining explained variance, visualizations, and clustering performance.
What is explained variance and why is it important?
Explained variance measures how much information is retained after reduction. It's crucial for understanding data loss.
Can you suggest some visualization techniques for this?
Sure! You can use scatter plots, biplots, or heatmaps to visualize the results of dimension reduction.
How do I assess clustering performance after reduction?
You can use metrics like silhouette score, Davies-Bouldin index, or visual inspection of clusters to assess performance.
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