first phase of Chadhuri's clusting algorithm
finished first draft of chaudhuri algorithm
check intersection of compact paris in partition function:
normalized Affine checks for length 0, resolves #28
finished implementing all cases for calculateSparsenessThreshold in clustering.py
added tests to canonical_example for clustering - getting good results
Merge pull request #27 from open-city/clustering

We are implementing clustering of pairwise duplicates using Chadhuri's clusting algorithm
divide by sum of length of strings for normalization
ouputting clustered list of dupes
printing all rows to csv, using bigger numbers for percent estimated dupes and neighborhood
split off address in to street and zip, increased number of training pairs
finished test run with good results
candidates should appear in one and only one cluster, closes #29
applied forests clustering bugfix
final run before data party
second draft of clustering.py
finished rewrite of clustering
added function to read and write learned settings to file, closes #30
simpler normalized affinegap where we just divide by the sum of the length of the two strings performs better than Yu's approach
update affinegap.c