abstract revised for KMeans.ipynb

doc/ipython-notebooks/clustering/KMeans.ipynb

@@ -1,6 +1,7 @@
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@@ -27,7 +28,7 @@
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-      "In this notebook we are going to see how Shogun Machine Learning Toolbox can be used for clustering with KMeans. In particular, we will be discussing the various options/choices provided to a user by the KMeans implementation in Shogun. "
+      "This notebook demonstrates <a href=\"http://en.wikipedia.org/wiki/K-means_clustering\">clustering with KMeans</a> in shogun along with it's initialization and training. The initialization of cluster centres is shown manually, randomly and that from using <a href=\"http://en.wikipedia.org/wiki/K-means%2B%2B\">KMeans++</a> algorithm. The training is shown using Classical <a href=\"http://en.wikipedia.org/wiki/Lloyd%27s_algorithm\">Lloyd</a> and mini-batch Kmeans method. Finally it is worked upon a Real dataset, further adding <a href=\"http://en.wikipedia.org/wiki/Principal_component_analysis\">PCA</a> to to its cause."
      ]
     },
     {