The training continuation for saved LDA model

Current online implementation of the LDA model fit (OnlineLDAOptimizer) does not support the model update (ie. to account for the population/covariates drift) nor the continuation of model fitting in case of the insufficient number of iterations.

Technical aspects:

1. The implementation of LDA fitting does not currently allow the coefficients pre-setting (private setter), as noted by a comment in the source code of OnlineLDAOptimizer.setLambda: "This is only used for testing now. In the future, it can help support training stop/resume".

2. The lambda matrix is always randomly initialized by the optimizer, which needs fixing for preset lambda matrix.

The adaptation of the classes by the user is not possible due to protected setters & sealed / final classes.