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1 parent 525dc1f commit 92fe82eb182566601610da9ad42703eb553959b7 @ogrisel ogrisel committed Apr 25, 2011
Showing with 8 additions and 8 deletions.
  1. +8 −8 doc/modules/clustering.rst
@@ -1,8 +1,8 @@
.. _clustering:
`Clustering <>`__ of
unlabeled data can be performed with the module :mod:`scikits.learn.cluster`.
@@ -83,7 +83,7 @@ of cluster. It will have difficulties scaling to thousands of samples.
Spectral clustering
:class:`SpectralClustering` does a low-dimension embedding of the
affinity matrix between samples, followed by a KMeans in the low
@@ -163,13 +163,13 @@ connectivity constraints are added between samples: it considers at each step
all the possible merges.
-Adding connectivity constraints
+Adding connectivity constraints
An interesting aspect of the :class:`Ward` object is that connectivity
constraints can be added to this algorithm (only adjacent clusters can be
merged together), through an connectivity matrix that defines for each
-sample the neighboring samples following a given structure of the data. For
+sample the neighboring samples following a given structure of the data. For
instance, in the swiss-roll example below, the connectivity constraints
forbid the merging of points that are not adjacent on the swiss roll, and
thus avoid forming clusters that extend across overlapping folds of the
@@ -201,10 +201,10 @@ enable only merging of neighboring pixels on an image, as in the
.. topic:: Examples:
- * :ref:``: Ward clustering
+ * :ref:``: Ward clustering
to split the image of lena in regions.
- * :ref:``: Example of
+ * :ref:``: Example of
Ward algorithm on a swiss-roll, comparison of structured approaches
versus unstructured approaches.

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