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General review and plenty of changes
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@T-Flet T-Flet released this 30 Nov 18:24
· 6 commits to master since this release
v1.0.3
63aa3a8

  • Re-implementation:

    • Base sigmoidal kernels: computationally more efficient; no more warnings and enforced ceilings now gone
    • Change operators: fit appreciably better (i.e. competitive where the data is truly of that kind), probably partly due to steeper gradients of new functional form
    • Periodic Kernel: replicated the series-expansions-based approximations as in GPML MATLAB library instead of the pure-form version with overflow-prevention

  • Restructuring:

    • Kernel Expressions: the classes are now code-wise more separate (still modular), and the Sigmoidal * Constant expression simplification is now prevented (for description generation)
    • Internal functions passing: model-scoring and model-list fitting functions are now passed directly (and can therefore be supplied by a user)
    • External (exported) starting kernels, rules and search parameters: added a few and better organised starting kernels and groups of production rules for easy user selection (arbitrary inputs still allowed)
    • Global configurations grouped in config.py; may become more user-controllable (e.g. as search arguments) in the future

  • Remaining issues:

    • The Periodic kernel is still somehow unstable but competitive when data is not periodic; it seems this is its actual nature
    • Stationary kernels in ChangeWindow kernels do not work well (which make sense, but it would be nice if it could be remedied); could try adding a more-or-less hidden offset between the two sides (for all or only non-stationary kernels) in the future
Assets 2