- Linear least-squares regression (curve fitting).
- 2D convex hulls.
- Delaunay triangulation.
- k-means algorithm for machine learning with example data.
- Longest common subsequence and Levenshtein edit distance.
- Root finding.
- Parallel aggregates: mapReduce, reduce, minBy, maxBy, tryPick, tryFindIndex, exists and forall.
Existing customers can download the latest .NET assembly and an F# script providing extensive worked examples for free.
As always, the new features are designed for ease of use and integrate seamlessly with our F# for Visualization library. Convex hull: