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KNN Demo

AIO2025: Module 03.

๐ŸŽฏ How to Use: Select data โ†’ Configure target โ†’ Set parameters โ†’ Enter new point โ†’ Run prediction!

Start with sample datasets or upload your own CSV/Excel files.

๐Ÿ—‚๏ธ Sample Datasets
๐ŸŽฒ Problem Type
๐ŸŽฏ Target Column

๐Ÿ”„ Loading sample data...

๐Ÿ“‹ Data Preview (First 5 Rows)

๐Ÿ“ Algorithm Parameters

๐Ÿ“ Distance Metric
โš–๏ธ Weighting Method

๐Ÿ“Š Results & Visualization

๐ŸŽฏ Prediction Result

Run prediction to see the result.

๐Ÿ‘ฅ Nearest Neighbors Details

๐Ÿ“‹ Algorithm Summary

Algorithm details will appear here after prediction.

๐Ÿ’ก Tips:

  • High-dimensional data automatically uses t-SNE for 2D visualization.
  • Orange circles show visually closest points, black diamonds show algorithm-accurate neighbors.
  • Try different K values and distance metrics to see how results change!