| jaccard_hyper_grid_search {zoomerjoin} | R Documentation |
Help Choose the Appropriate LSH Hyperparameters
Description
Runs a grid search to find the hyperparameters that will achieve an (s1,s2,p1,p2)-sensitive locality sensitive hash. A locality sensitive hash can be called (s1,s2,p1,p2)-sensitive if to strings with a similarity less than s1 have a less than p1 chance of being compared, while two strings with similarity s2 have a greater than p2 chance of being compared. As an example, a (.1,.7,.001,.999)-sensitive LSH means that strings with similarity less than .1 will have a .1% chance of being compared, while strings with .7 similarity have a 99.9% chance of being compared.
Usage
jaccard_hyper_grid_search(s1 = 0.1, s2 = 0.7, p1 = 0.001, p2 = 0.999)
Arguments
s1 |
the s1 parameter (the first similaity). |
s2 |
the s2 parameter (the second similarity, must be greater than s1). |
p1 |
the p1 parameter (the first probability). |
p2 |
the p2 parameter (the second probability, must be greater than p1). |
Value
a named vector with the hyperparameters that will meet the LSH criteria, while reducing runitme.
Examples
# Help me find the parameters that will minimize runtime while ensuring that
# two strings with similarity .1 will be compared less than .1% of the time,
# strings with .8 similaity will have a 99.95% chance of being compared:
jaccard_hyper_grid_search(.1, .9, .001, .995)