Initial release candidate for version 2.0.0

What’s New:
Time series functionality:

• Addition of time series models implemented in q
  • AR, ARMA, ARIMA, SARIMA and ARCH.
• Time series feature engineering techniques (windowed and lagged feature generation.
• Data stationarity testing

Graph/pipeline resources:

• Framework for the development of modularised kdb+ workflows and executable pipeline structures

Optimization:

• Implementation of the Broyden-Fletcher-Goldfarb-Shanno algorithm for function minimization

Grid Search:

• Random and pseudo random (Sobol) number generated parameter set functionality providing an alternative to exhaustive grid search.
  Clustering:
• Implementation of k-means clustering now uses early stopping

Updates:

Clustering:

• Fit / predict / update style function calls rather than just fit+predict as previously to allow models to be deployed for classification on incoming data.