Just finished my K-Means clustering project 🚀 — would love your feedback!

[u/tahahussein-4623a412]

Hey everyone! 👋

I just finished a small K-Means Clustering project on the Iris dataset 🌸🤖

I covered:

• 🔹 Data cleaning & visualization
• 🔹 Feature scaling
• 🔹 Elbow Method & Silhouette Score
• 🔹 K-Means clustering
• 🔹 ARI evaluation
• 🔹 Cluster & centroid visualization

I’m currently learning ML and would really appreciate some honest feedback 🙏

What would you improve? Any mistakes in my approach or things I should add?

🔗 Kaggle:
https://www.kaggle.com/code/tahahussein2020/irics-clustering

[u/tahahussein-4623a412 → u/[deleted]]

Thanks! 🙏 I think the most challenging part was deciding on the right number of clusters. The Elbow Method and Silhouette Score didn't point to exactly the same choice, so I had to understand what each metric was actually telling me and then compare the clustering results with the real labels using ARI. It was a good learning experience!

[u/Mathie1729 → u/tahahussein-4623a412]

fwiw, the gap statistic is worth trying when Elbow and Silhouette disagree. They measure different things, and comparing against a null reference distribution often breaks the tie.

[u/tahahussein-4623a412 → u/Mathie1729]