* DOC examples with correct notebook style
* Modifications in examples/ to avoid unwanted notebook style
* Remove last notebook style example
* Space formatting to avoid notebook style
In the Matplotlib 'Specifying Colors' section, neither list nor array is a valid color specification type. When this example is run using Python 3.5, and matplotlib 2.0.2 (latest), it errors with the message:
"ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()"
This change preserves the semantics of the example while allowing it to successfully run by converting to tuples for the matplotlib color specification.
* Adding GMM to plot_cluster_comparison.py and changing number of components in all algos to 3.
* adding two datasets to clustering comparision example
* Adding GMM to plot_cluster_comparison.py and changing number of components in all algos to 3.
* adding two datasets to clustering comparision example
* GMM example using GaussianMixture
* fixing lint errors; changing order of datasets in the columns so that no_structure is at the end.
* adding warning supression.
* fixing warning supression.
* hand-tuned cluster parameters
* moved list of algo names; cleaning up color cycling
* fixing islice stop to be an int
* change default to params, make plot color-blind compatible, fix spelling error
* new color palette that is more color-blind friendly
The comment in a few example plots refer to "the mesh [x_min, m_max] x
[y_min, y_max]" when it should be "x_max".
Also fixed the spacing in plot_random_forest_embedding.py `[x_min,
x_max] x [y_min, y_max]` to `[x_min, x_max]x[y_min, y_max]` to comply
with the coding style of other files with similar code (like those in
the current pull request).
1. Fix condition for checking threshold.
2. Fix the global clustering by remapping the samples to the
subcluster_centers.
3. Add tests for threshold.
4. Minor doc and cosmits.
1. Added partial_fit and predict methods
2. Inherit from ClusterMixin from fit_predict methods
3. Removed inplace modification of X and self.copy
4. Added final global clustering and n_clusters param.
1. Improved documentation.
2. Added sanity test.
3. Moved example to a separate folder
4. Optimised compuation of centroids.
5. Added underscore to public attributes.
Vrishank Bhardwaj
Hanmin Qin