The third example illustrates k-means on the common Iris dataset. Because the data has four dimensions, we perform a principle components analysis (PCA) to reduce to two dimensions (the two most important components) to plot the data.
======================= K-Means Iris Clustering ======================= Cluster the common iris dataset. To visualise the data we first do a principle component analysis to map to the two most important components, to suit a 2D plot which we display. The points are coloured according the the iris species. Close the graphic window using Ctrl-W. Press Enter to continue:
Next we visualise the algorithm clustering this dataset. Close the graphic window using Ctrl-W. Press Enter to exit:
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