Online Algorithms for Statistics, Models, and Big Data Viz
Online algorithms are well suited for streaming data or when data is too large to hold in memory. OnlineStats processes observations one by one and all algorithms use O(1) memory.
import Pkg Pkg.add("OnlineStats") using OnlineStats o = Series(Mean(), Variance(), P2Quantile(), Extrema()) fit!(o, 1.0) fit!(o, randn(10^6))
- Trivial PRs such as fixing typos are very welcome!
- For nontrivial changes, you'll probably want to first discuss the changes via issue/email/slack with
See also the list of contributors to OnlineStats.
MIT - see the LICENSE file.