KnowledgeHub
Questions
Tags
Users
Search
Alex Rivera
|
Logout
Edit Question
Title
Body
I am trying to ascertain how VowpalWabbit's "state" is maintained as the size of our input set grows. In a typical machine learning environment, if I have 1000 input vectors, I would expect to send all of those at once, wait for a model building phase to complete, and then use the model to create new predictions. In VW, it appears that the "online" nature of the algorithm shifts this paradigm to be more performant and capable of adjusting in real-time. How is this real-time model modification implemented ? Does VW take increasing resources with respect to total input data size over time ? That is, as i add more data to my VW model (when it is small), do the real-time adjustment calculations begin to take longer once the cumulative # of feature vector inputs increases to 1000s, 10000s, or millions?
Tags (comma-separated)
Save Edits
Cancel