Dear all, Per my understand, what Feature Hashing did in SGD do compress the Feature Dimensions to a fixed length Vector. Won't that make the training result incorrect if Feature Hashing Collision happened? Won't the two features hashed to the same slot would be thought as the same feature? Even if we have multiple probes to reduce the total collision like a bloom filter. Won't it also make the slot that has the collision looks like a combination feature?
Thanks. Best wishes, Stanley Xu
