F#

Based on pythonnet/pythonnet#554

> #r C:\\Python\\Python35_64b\\lib\\site-packages\\Python.Runtime.DLL
> using Python.Runtime;
> dynamic np; using (Py.GIL()) { np = Py.Import("numpy");};
> using System.Collections.Generic;
> using System.Collections;
> dynamic a = np.array(new List<float> { 1, 2, 3 });
> dynamic b = np.array(new List<float> { 6, 5, 4 }, dtype:

This is to track implementation of the ML-Features: https://spark.apache.org/docs/latest/ml-features

Bucketizer has been implemented in dotnet/spark#378 but there are more features that should be implemented.

• Feature Extractors
  • TF-IDF
  • Word2Vec (dotnet/spark#491)
  • CountVectorizer (https://github.com/dotnet/spark/p

There’s a repository targeted at comparing shrinking behaviour of various PBT libraries: https://github.com/jlink/shrinking-challenge

Would be great to have FsCheck therein. We’re happy to take PRs.

In Statistics module, we do calculations and it would be beneficial to cover it by unit or property-based tests.

Here you can take a look at examples with property-based testing.