Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/13176#discussion_r64535542
--- Diff: docs/ml-features.md ---
@@ -53,7 +53,10 @@ collisions, where different raw features may become the
same term after hashing.
chance of collision, we can increase the target feature dimension, i.e.
the number of buckets
of the hash table. Since a simple modulo is used to transform the hash
function to a column index,
--- End diff --
Should we also mention that we use ``` Austin Appleby's MurmurHash 3
algorithm``` to calculate the hash code value? Because how to set the feature
dimension is related with the hash algorithm.
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