Update FAQ.

kernelmethod · kernelmethod · commit 40c7d8a9b146 · 2020-01-18T03:21:20.000-07:00
diff --git a/docs/src/faq.md b/docs/src/faq.md
@@ -44,7 +44,7 @@ julia> for uh in unique(hashes)
 12
 ```
 
-Our hash function has generated 3 unique 20-bit hashes, with 72 points sharing the first hash, 16 points sharing the second hash, and 12 points sharing the third hash. That's not a great split, but could still drastically reduce the size of the search space. For instance, the following benchmarks (on an Intel Core i7-8565U @ 1.80 GHz) suggest that the cost of computing [`SimHash`](@ref) on 10-dimensional data is about 34 times the cost of computing [`cossim`](@ref):
+Our hash function has generated 3 unique 20-bit hashes, with 72 points sharing the first hash, 16 points sharing the second hash, and 12 points sharing the third hash. That's not a great split, but could still drastically reduce the size of the search space. For instance, the following benchmarks (on an Intel Core i7-8565U @ 1.80 GHz) suggest that the cost of computing 20-bit [`SimHash`](@ref) on 10-dimensional data is about 34 times the cost of computing [`cossim`](@ref):
 
 ```
 julia> using BenchmarkTools

Original file line number	Diff line number	Diff line change
`@@ -44,7 +44,7 @@ julia> for uh in unique(hashes)`
`44`	`44`	`12`
`45`	`45`	```
`46`	`46`
`47`		-Our hash function has generated 3 unique 20-bit hashes, with 72 points sharing the first hash, 16 points sharing the second hash, and 12 points sharing the third hash. That's not a great split, but could still drastically reduce the size of the search space. For instance, the following benchmarks (on an Intel Core i7-8565U @ 1.80 GHz) suggest that the cost of computing [`SimHash`](@ref) on 10-dimensional data is about 34 times the cost of computing [`cossim`](@ref):
	`47`	+Our hash function has generated 3 unique 20-bit hashes, with 72 points sharing the first hash, 16 points sharing the second hash, and 12 points sharing the third hash. That's not a great split, but could still drastically reduce the size of the search space. For instance, the following benchmarks (on an Intel Core i7-8565U @ 1.80 GHz) suggest that the cost of computing 20-bit [`SimHash`](@ref) on 10-dimensional data is about 34 times the cost of computing [`cossim`](@ref):
`48`	`48`
`49`	`49`	```
`50`	`50`	`julia> using BenchmarkTools`