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Accord.NET v2.14.0 Release Notes

Release Date: 2014-12-08 // over 9 years ago

  • 🚀 > Build 2.14.1.5087, released on 15.12.2014

    🚀 Accord.NET Framework 2.14.0 release notes

    15.12.2014.

    🔖 Version updates and fixes:

    • GH-29: HiddenConditionalRandomField is not correctly serialized;
    • GH-31: Adding hidden Markov Model methods for computing the probability of
      a state assuming a particular value inside an observation sequence;
    • GH-36: Extensions class collides with the Accord.NET Extensions Framework;
    • GH-35: Distribution issue with .NET 3.5 assemblies;
    • GH-37: Adding Taylor series functions and dissimilarity functions;
    • GH-42: Adding new contributed distance functions;
    • 👍 GH-46: Optimization functions and constraints to now support different cultures;
    • 🌲 GH-48: Fix calculation of log likelihoods for BaumWelch learning algorithm;
    • GC-33: GoldfarbIdnaniQuadraticSolver class failed to give correct answer.
    • Accord.Core
      • Adding Red-Black trees and a Red-Black dictionary based on those trees
        👍 with support for efficiently searching for maximum and minimum elements.
    • Accord.IO
      • Updating the IDX reader to automatically convert between different data types.
    • Accord.Math
      • Adding the Nelder-Mead and Subplex non-linear optimization algorithms;
      • Adding matrix padding methods (adding extra rows and columns with zeros);
      • Updating quadratic optimization constraints to support tolerance parameters.
    • Accord.Statistics
      • Adding regularization in IterativeReweightedLeastSquares;
      • Adding DistributionAnalysis for estimating distributions from observed data;
      • Adding weighted measure methods in Statistics.Tools that are
        based on element repetitions rather than element importance;
      • Adding Anderson-Daring, Shapiro-Wilk, Inverse Chi-Square, Lévy, Folded
        🌲 Normal, Shifted Log-Logistic, Kumaraswamy, Trapezoidal, U-quadratic and
        BetaPrime distributions;
      • Adding Anderson-Daring and Shapiro-Wilk hypothesis tests;
      • Correcting the MarkovMultivariateFunction constructor for
        explicit Independent hidden Markov models;
      • Correcting discrete Viterbi learning convergence check and unifying
        the Viterbi implementations for discrete and continuous variables;
      • Correcting the calculation of log likelihoods in Baum Welch learning;
      • Correcting serialization issue with DynamicTimeWarping kernel;
      • Updating all distribution functions constructors to offer Range attributes
        that can be used to automatically determine valid values for its parameters;
      • Updating Logistic Regression and Cox's Proportional Hazards
        ✅ analyses to avoid computing LR-ratio tests unless necessary;
      • Updating Multivariate Empirical Distributions to support CDF;
      • Updating Empirical Distributions to support weighted samples;
      • Updating CRF output feature functions to activate only once per sequence;
      • Updating all probability distributions to offer a Generate method;
      • Updating ChiSquare Test to support testing against continuous distributions;
      • Updating univariate discrete distributions with Quantile Density functions.
    • Accord.MachineLearning
      • Adding LIBLINEAR's linear support vector regression (SVR) algorithms;
      • Adding LinearCoordinateDescent for the primal formulation and renaming the
        previous coordinate descent algorithm to LinearDualCoordinateDescent;
      • Adding named constructors in Naive Bayes to build Gaussian models more easily;
      • Updating Naive Bayes classifiers to estimate component variables in parallel;
      • Updating ID3 algorithm so attributes can join multiple times a decision;
      • Updating Bag-of-Visual-Words to avoid computing costly cluster measures;
      • Updating K-Means to support setting algorithm options through its class itself;
      • Updating K-NearestNeighbor feature matching to use KD-Trees when its possible;
      • Updating error-based pruning to avoid computing modes when there are no elements;
      • Updating K-Modes to select modes per column, instead of entire elements. Now it
        is also possible to use the Kmeans++ initialization scheme in this algorithm.
    • Accord.Neuro
      • Adding Rectified Linear activation functions.
    • Accord.Imaging
      • Fixing Niblack and Sauvola thresholding algorithms for 8bpp images.
    • Accord.Audio
      • Adding a Volume adjustment filter for audio signals.
    • Accord.Controls
      • Adding a DataBarBox visualization box;
      • Updating visualizations to offer more flexibility in customizing ZedGraph charts;
    • Sample applications
      • Adding support for adjusting volume in the Recorder sample application.