Accord.NET v3.4.0 Release Notes

Release Date: 2017-01-11 // about 7 years ago
  • 🚀 > Build 3.4.0.5853, released on 14.01.2017

    🚀 Accord.NET Framework 3.4.0 release notes

    14.01.2017.

    🔖 Version updates and fixes:

    • GH-19: Implement Grubbs' test;
    • GH-129: Possible error in Special.BSpline function;
    • GH-153: Visual Studio 2015;
    • GH-172: Add Random Forest Implementation;
    • GH-177: AugmentedLagrangian with NonlinearConstraints - Gradient NullReferenceException issue;
    • GH-183: Severity Check in NumberOfVertices Set Property on DiscreteCurveEvolution Class;
    • 🏗 GH-229: Can't build cloned repository;
    • GH-250: Prediction interval - Accord.Statistics.Models.Regression.LogisticRegression;
    • GH-264: Integer division instead of double in GetSpectralResolution;
    • GH-264: Incorrect use of loop variables in sample converter;
    • GH-264: Checking same arguments multiple times in blob counter;
    • GH-264: Checking length of same vector in a loop;
    • GH-264: Integer division instead of double in Math.Tools;
    • GH-264: Dependency classes of Denavit Harternberg IK solver should be marked as Serializable;
    • GH-264: Error when checking whether component mixtures implement IFormattable;
    • GH-264: Multivariate Empirical Distribution outdated/unecessary argument checks;
    • 👍 GH-264: Correcting the support for weighted samples in Inverse Gaussian Distribution;
    • GH-275: Examples for the GoldfarbIdnani solver are not up to date and do not compile;
    • GH-291: Accord.Imaging nuget dependencies;
    • GH-295: Accord.Video.FFMPEG.VideoFileWriter ignores bitrate;
    • 📚 GH-296: Update documentation for hidden Markov models;
    • ⚡️ GH-299: Update to .NET 4.6 and VS2015;
    • GH-302: Regression (SVMs) : NullReferenceException on clicking 'Create Machine';
    • 🚀 GH-309: Compile error with release 3.2.2;
    • GH-310: Examples for L1-regularized (Logistic) regression;
    • GH-313: Inaccuracy in Accord.Math Pseudoinverse;
    • GH-314: V3.3.0 Cannot set input and output names in LogisticRegressionAnalysis;
    • GH-320: Shared Covariance Matrix for Gaussian Mixture Models;
    • GH-325: ClusterCollection doesn't implement IEnumerable properly (runtime error);
    • GH-327: NegativeBinomialDistribution Cum Dist func not returning expected value;
    • GH-301: Bug in Accord.Statistics.Analysis.DistributionAnalysis
    • GH-304: Bug in GammaDistribution.ProbabilityDensityFunction
    • GH-330: Liblinear (Linear SVMs) does not train, exits with "index out of range";
    • GH-331: RandomForest is not serializable;
    • GH-332: Partial Least Squares issue with NIPALS method and the new API;
    • GH-337: ExpectationMaximization max Iterations can't be changed;
    • GH-340: PoissonDistribution InverseDistributionFunction not returning expected value;
    • GH-365: Can HOG to work with BoW'2 with SVM or OSVM.
    • General
      • Fixing make install on Linux/Mono.
    • Imaging
      • Updating BagOfVisualWords to implement the updated IBagOfWords interface;
      • Adding methods to facilitate the creation of BoVW with arbitrary extractors;
      • Adding examples in the documentation on how to learn SVMs on the extracted Bo(V)Ws;
      • Updating IFeatureDetector interfaces to use covariance and contravariance to avoid element-by-element type conversions.
    • Math
      • Adding support for computing the full QR decomposition (besides only the economy one);
      • Adding methods to compute the null-space of a given matrix.
    • MachineLearning
      • Updating the IBagOfWords interface and implementing classes to implement the IUnsupervisedLearning and ITransform interfaces;
      • Updating ZeroOneLoss to handle class labels in the -1/+1 format;
      • Updating the kernel cache to pre-compute the entire kernel matrix by default.
    • Statistics
      • Adding random generators for the von-Mises Fisher distribution;
      • Updating documentation examples for Hidden Markov Models, Hidden Markov Classifiers and their respective algorithms;
      • Adding a new GammaOptions class to pass fitting options to Gamma distributions;
      • Updating DistributionAnalysis to use the new machine learning interfaces/API;
      • Updating code and documentation for Dynamic Time warping kernel;
      • Updating Gamma distribution so probabilities are computed in the log-domain by default;
      • Marking Moving and Running statistics as ISerializable;
      • Adding methods to compute the marginals in multivariate discrete distributions;
      • Adding RunningRangeStatistics and MovingRangeStatistics.