New custom exception added.

Modified the launcher to handle new options and the executions of
different programs.

Modified the KNN to handle non-integer minkowski's distances.
Redone the launcher, to support different methods.
Normalization done.

Fixed: getting the min and max values.

Added: Now, we can modify the attributes of an instance. This was needed
for the normalization.

Modified: Changed the instantiation of the centroid. Now it's not
required to provide a serial number, as it won't be treated as an
instance.

Removed: ModifyCentroid method. This functionality is provided by
Instance Superclass
Deleted the Centroid class.
Changed every ArrayList for LinkedList in order to be used properly with
KNN
Modified some parts of the code to simplify it
Documentation updated, some refactoring done
Deleted things
files addded
My version of KMeansClustering
Changed the dissimilarity method and improved the iterations method
Fixed the normalization and merged the two methods of the Kmeans. Now
the method is the same, but the condition of stopping is different.
Finished the dissimilarity calculation
Fixed the cases where an instance is not classified and an error in the
KNN when we have already checked all the neighbours and the data
structure was empty.
Added a class for managing the clustering techniques.

Fixed a lot of bugs and added the method to visualize the output of the
clustering (not finished)
Added a result visualization. Fixed more bugs, Now KMeansClustering
returns the final centroids.
Fixed the dissimilarity method.
Changes in the documentation
Test bibliography
docu actualizada
Merge branch 'K_Means_Clustering' of https://github.com/RubenAgudo/MineriaDatos.git into K_Means_Clustering