
                       README for the Examples Directory
                       *********************************

The Examples directory contains the following scripts:


    1.  LSH_basic_for_demonstrating_nearest_neighbors.py

            This script demonstrates the functionality one traditionally associates
            with the LSH algorithm --- finding nearest neighbors.  This script places
            the user in an interactive session in which the user is asked to enter
            the symbolic name of a data record in the datafile that was processed by
            the LSH algorithm.  Subsequently, the user is shown the nearest neighbors
            of that record.


    2.  Clustering_with_LSH_with_sample_based_merging.py

            This is one of the two scripts in the Examples directory that attempt to
            cluster the data that is supplied to the module through a CSV file. The
            data is clustered on the basis of the neighborhoods supplied by the LSH
            algorithm.  If the coalescence of the LSH generated neighborhood creates
            more cluster than expected, this script calls on the
            merge_similarity_groups_with_l2norm_sample_based() to merge excess small
            clusters with the main retained clusters.


    3.  Clustering_with_LSH_with_set_based_merging.py     

            This is the second of the cluster producing scripts in the Examples
            directory.  Again, the starting points for forming the clusters are the
            neighborhoods supplied by the LSH algorithm.  Unlike the previous script,
            this script calls on the merge_similarity_groups_with_l2norm_set_based()
            to merge excess small clusters with the main retained clusters.

    4.  gen_data.py

            This script uses the DataGenerator class that comes with the LSH module
            to generate multi-variate Gaussian data for experimenting with the LSH
            module.  The output file produced by this method can be used directly for
            input to the LSH class.
