2.0.0

• Gradient Boost now uses gradient-based subsampling
• Allow Token Hashing Vectorizer custom hash functions
• Gradient Boost base estimator no longer configurable
• Move dummy estimators to the Extras package
• Increase default MLP window from 3 to 5
• Decrease default Gradient Boost window from 10 to 5
• Rename alpha regularization parameter to L2 penalty
• Added RBX serializer class property type change detection
• Rename boosting estimators param to epochs
• Neural net-based learners can now train for 0 epochs
• Rename Labeled stratify() to stratifyByLabel()
• Added Sparse Cosine distance kernel
• Cosine distance now optimized for dense and sparse vectors
• Word Count Vectorizer now uses min count and max ratio DFs
• Numeric String Converter now handles NAN and INFs
• Numeric String Converter is now Reversible
• Removed Numeric String Converter NAN_PLACEHOLDER constant
• Added MurmurHash3 and FNV1a 32-bit hashing functions to Token Hashing Vectorizer
• Changed Token Hashing Vectorizer max dimensions to 2,147,483,647
• Increase SQL Table Extractor batch size from 100 to 256
• Ranks Features interface no longer extends Stringable
• Verbose Learners now log change in loss
• Numerical instability logged as a warning instead of info
• Added header() method to CSV and SQL Table Extractors
• Argmax() now throws an exception when undefined
• MLP Learners recover from numerical instability with a snapshot
• Rename Gzip serializer to Gzip Native
• Change RBX serializer constructor argument from base to level
• Rename Writeable extractor interface to Exporter