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mlpack v3.1.0 Release Notes

Release Date: 2019-04-26 // about 5 years ago

  • 🚀 Released April 25, 2019.
    🚀 Release email

    ➕ Add DiagonalGaussianDistribution and DiagonalGMM classes to speed up the diagonal covariance computation and deprecate DiagonalConstraint (#1666).

    ➕ Add kernel density estimation (KDE) implementation with bindings to other languages (#1301).

    Where relevant, all models with a Train() method now return a double value representing the goodness of fit (i.e. final objective value, error, etc.) (#1678).

    ➕ Add implementation for linear support vector machine (see src/mlpack/methods/linear_svm).

    🔄 Change DBSCAN to use PointSelectionPolicy and add OrderedPointSelection (#1625).

    👍 Residual block support (#1594).

    Bidirectional RNN (#1626).

    Dice loss layer (#1674, #1714) and hard sigmoid layer (#1776).

    output option changed to predictions and output_probabilities to probabilities for Naive Bayes binding (mlpack_nbc/nbc()). Old options are now deprecated and will be preserved until mlpack 4.0.0 (#1616).

    ➕ Add support for Diagonal GMMs to HMM code (#1658, #1666). This can provide large speedup when a diagonal GMM is acceptable as an emission probability distribution.

    Python binding improvements: check parameter type (#1717), avoid copying Pandas dataframes (#1711), handle Pandas Series objects (#1700).