Accord.NET Framework 3.4.0

@cesarsouza cesarsouza released this Jan 11, 2017

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  • GH-264: Multivariate Empirical Distribution outdated/unecessary argument checks;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.

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Accord.NET Framework 3.3.0

@cesarsouza cesarsouza released this Sep 16, 2016 · 215 commits to development since this release

Build 3.3.0.5736, released on 17.09.2016

Accord.NET Framework 3.3.0 release notes

17.09.2016.

Version updates and fixes:

  • GC-62: Add support for computing prediction intervals in linear and generalized linear models
  • GH-113: System.AggregateException thrown in C45Learning.Run;
  • GH-115: Add documentation about how to work with sparse data;
  • GH-130: Multi class support vector machine doesn't work with SparseGaussian kernel;
  • GH-139: Examples using explicit kernel matrices;
  • GH-178: DecisionTreeWriter uses local CultureInfo when writing values;
  • GH-249: Potential bug in RandomForest or C45Learning;
  • GH-201: Adding Generalized Pareto Distribution;
  • GH-245: Incorrect method usage in Distance.GetDistance;
  • GH-255: Adding examples on how to use Laplace rule in Naive Bayes learning;
  • GH-253: BlobCounter needs a IDisposable implementation;
  • GH-252: Bug in Kurtosis Contrast Function;
  • GH-270: Adding example to show to use continuous variables in C4.5;
  • GH-271: OneclassSupportVectorLearning does not use shrinking heuristics property;
  • GH-281: Possible bug in GammaDistribution generation function when k < 1;
  • GH-282: Issue in LogisticRegression.Transform() returns true for all inputs;
  • GH-280: Merge pull request #280 from fch-aa/Fix-SMO-CacheSize;
  • GH-278: Merge pull request #278 from kulov/development;
  • GH-272: Merge pull request #272 from kdbanman/GH-271;
  • GH-269: Merge pull request #269 from mikhail-barg/minor-fix;
  • GH-273: VideoFileWriter not working;
  • GH-274: Merge pull request #274 from hzawary:development;
  • GH-285: Deserialize of Codification error in 3.2.0;
  • GH-286: Ransac - possible bug in calculation of 'N' if pInlier = 0;
  • GH-288: NaiveBayes issue when probability is 0;
  • GH-289: Incorrect use of GetLength(0) for jagged arrays in Matrix class.
  • General
    • This will be last release that includes an executable installer. If you
      are still using the installer, please move to NuGet or use the framework
      compressed archive files.
  • Imaging
    • Creating a new Accord.Imaging.Noncommercial assembly to hold non-commercial imaging methods;
    • Adding Fast Guided Filter to Accord.Imaging.Noncommercial.
  • MachineLearning
    • Fixing Binary Split's learn method to accept null weights;
    • Updating Binary Split example to reflect the new API;
    • Adding constructors to allow tree inducing algorithms to create a tree from scratch;
  • Statistics
    • Fixing multiple issues with statistical analyses classes when they are used using the
      new classification/regression APIs;
    • Statistical measures (Measures.cs) have been moved to the Accord.Math assembly,
      but have been kept under the Accord.Statistics namespace;
    • Correcting L2-regularization in Logistic Regression.

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Accord.NET Framework 3.2.0

@cesarsouza cesarsouza released this Aug 20, 2016 · 293 commits to master since this release

Build 3.2.0.5706, released on 20.08.2016

Accord.NET Framework 3.2.0 release notes

20.08.2016.

Accord.NET 3.2 "auto-generated" release

Version updates and fixes:

  • GH-76/GC-24: Add easier creating and handling of factors for categorical variables
  • GH-123: Bug in the Euclidean on Accord.Math.Distance
  • GH-124: Fixing the Envelop filter as missing loop variables were not being incremented
  • GH-135: When the from and to ranges are equal, scaled values should remain unchanged
  • GH-159: Gamma Distribution Fit stalls for some arrays
  • GH-162: ntdll on OS X
  • GH-167: Posterior method has wrong signature in continuous hidden Markov Models
  • GH-171: Quadratic Programming (Goldfarb-Idnani) NoPossibleSolution on possible problems
  • GH-188: ProbabilisticOutputCalibration Class Example Incorrect Object Name
  • GH-206: Chessboard distance is incorrect
  • GH-214: Bug found in ReplaceChannel filter
  • GH-215: Bug Found in DecisionTrees.Learning.ID3Learning.
  • GH-225: Independent Component Analysis not converging
  • GH-232: Bug in Levenshtein distance.
  • GH-234: The subset of observations corresponding to a decision node may contains duplicates
  • GH-235: The getMaxChild method returns the max grandchild
  • GH-236: Possibly-biased comparison between errors
  • GH-237: The subset of observations corresponding to a decision node may contains duplicates
  • GH-240: Re() and Im() function of ComplexMatrix generates a OutOfRangeException
  • General
    • In this release, the Matrix library from Accord.Math has been almost completely
      redesigned to make heavy use of automatic code generation. This results in more
      code reuse, more consistent interfaces and the availability of many methods which
      before were available only for Double to almost all native numerical types in the
      .NET Framework;
    • The framework now contains core classes and interfaces for defining classification
      and regression models and their respective learning algorithms, offering a more
      standard interface when using different parts of the framework;
    • The framework now offers a Accord.Serializer class that should be responsible for
      serializing and deserializing any object from the framework, and will take care of
      versioning in case of breaking changes between releases;
    • All AForge.NET namespaces have been finally moved to inside Accord.NET, although
      some functionality is still duplicate.
  • Core
    • Adding Interlocked operations (Increment, Add) for double values;
    • To<> universal converter can now convert jagged arrays;
    • Adding a common framework to unify all classification models, and all learning algorithms;
    • Integrating the AForge.NET Range classes in the framework, adding ByteRange;
    • Adding a common serialization mechanism to the framework to manage backwards compatibility;
    • All classes from Accord.MachineLearning.Structures have been moved into Accord.Collections;
    • Updating RedBlackTrees to implement the new base classes for tree structures;
    • Updating KD-Trees to implement the base classes for tree structures (introduces breaking changes).
  • Sample applications
    • Fixing wrong arguments in sample applications.
  • Math
    • Revamped matrix library making heavy use of code generation with T4 templates;
    • Matrix dot products, and elementwise operations are now auto-generated;
    • Renaming InnerProduct to Dot, and marking previous products as obsolete;
    • Vector Range, Scale and Interval are now auto-generated;
    • Standardizing the way Vectors, Matrices and Jagged matrices are created and handled
      in the framework;
    • Adding OneHot and KHot methods overloads for creating vectors using boolean masks;
    • Adding ArgMin and ArgMax methods to Vector, Jagged and Multidimensional matrices;
    • Re-implementing Matrix.Sum and Matrix.Product using T4 templates;
    • Breaking change: Sum() now computes the Sum over the entire matrix (before it needed
      to be done with Sum().Sum(). In order to compute the sum vector over rows, use matrix.Sum(0)
      and for columns, matrix.Sum(1);
    • Chessboard distance has been removed as it is the same as Chebyshev;
    • Moving AForge.NET's old Random classes into the framework, and marking them as deprecated;
    • Adding a log1pexp method for computing (1.0 + Math.Exp(-sum)) without loss of precision;
    • Adding new random generators based on Marsaglia's Ziggurat method;
    • Introducing a new, generic IRandomNumberGenerator interface so existing statistical
      distributions can be used as Random Number Generators;
    • Updating Matrix.IsEqual method to use the auto-generated overloads if possible;
    • Replacing the previous framework-wide generator with a better API;
    • Improving the framework-wide random number generator so generators created in short
      timespans do not get initialized with the same seed: Now, updating a seed will not
      affect existent random generators in other threads. It will affect only newly created
      generators and the one in the current thread;
    • Fixing the DiagonalMatrix property in SingularValueDecomposition and
      JaggedSingularValueDecomposition so the returned diagonal matrices has the necessary
      dimensions to reconstruct the original matrix using the decomposition main formulation;
    • Fixing a bug in Combinatorics.Sequences method where the current vector would be returned
      instead of a copy when inPlace = false;
    • Distance functions can now be auto-generated from classes from the framework;
    • Adding Dice, Jaccard, Kulczynski, Matching, Rogers-Tanimoto, Russel-Rao, Sokal Michener,
      Sokal Sneath, Yule, Bhattacharyya and LogLikelihood distances as proper classes;
    • Updating IsEqual to support absoluete and relative tolarance thresholds;
    • Adding a Histogram method for creating a histogram from an array of integer values;
    • Updating the Interval, Range and Scale method overloads to be automatically generated;
    • Adding loss functions to be used in the unified framework;
    • Moving the Elementwise class to a separate Accord.Math.Core project in order to avoid
      excessive build times due the number of auto-generated methods in this class;
    • Adding overloads to Eigenvalue decomposition to automatically sorter eigenvectors and
      eigenvalues in descending order of absolute eigenvalue;
    • Adding a dedicated Sort static class with ordering-related methods such as Partition,
      Introsort and NthElement.
    • Expanding decompositions with two additional methods: GetInformationMatrix and Reverse
      GetInformationMatrix can be used to retrieve the standard errors for each coefficient
      when solving a linear system; Reverse reconstructs the original matrix using the definition
      of the decomposition;
    • Deprecating Submatrix in favor of Get (methods with non-inclusive last indices);
    • Adding ArgSort function for retrieving the indices that can be used to sort a vector;
    • Adding LogSumExp to the set of special functions.
  • MachineLearning
    • Adding a base foundation to encompass all classification and regression models in the
      framework as well as their learning algorithms: common interfaces and base classes for
      classifiers, distance-based classifiers and generative classifiers; common interfaces
      and base classes for supervised and unsupervised learning algorithms;
    • Updating Support Vector Machines, Decision Trees, Naive Bayes, Regressions and Analyses
      to use the new classes;
    • Unifying Linear and Kernel SupportVectorMachines, updating their classes to accept the
      Kernel function as a generic parameter: when the kernel function is a ValueType, this
      forces generic classes to be compiled specifically for each kernel type, allowing for
      the inlining of the kernel function calls;
    • Updating the way compact SVMs are represented: instead of having only a weight vector
      and no support vectors, compact machines have a single support vector and a single weight
      of value one, eliminating what before was a special case;
    • Adding classes for OneVsOne and OneVsRest classifiers, separating the functionality that
      was previously inside MulticlassSupportVectorMachine and MultilabelSupportVectorMachine;
    • Fixing multiple issues with ErrorBasedPruning (YaronK);
    • Updating GridSearch to implement ToString methods for easier debugging;
    • Updating Linear machines and learning algorithms to accept sparse kernels;
    • Deprecating the previous sparse vector implementations and moving the current implementation
      to the existing Linear class, since they represent the same operation;
    • Adding a true implementation for LibSVM-style Sparse vectors;
    • Updating SparseReader to read sparse vectors using the new Sparse representation;
    • Refactoring the clustering namespace to increase code reuse between the different algorithms;
    • Updating K-Means, GMM and BagOfWords to expose a ParallelOptions object that can
      be used to configure and stop the parallelization of those algorithms;
    • Updating K-Means to support sample weights;
    • Correcting multiple random initializations of Gaussian mixture model;
    • Adding a PriorityQueue class based on the MIT-licensed code by Daniel "BlueRaja" Pflughoeft.
    • Adding Vantage-Point and Space-Partitioning trees and Barnes Hutt t-SNE based on the original
      code from Laurens van der Maaten BH t-SNE implementation;
    • Adding a basic implementation for the Apriori algorithm.
  • Imaging
    • Updating static methods in AForge.NET's Image class to become extension methods;
    • Implementing ICloneable in all corner and feature detectors.
  • Neuro
    • Updating ResilientBackpropagation with the improvements from iRProp+.
  • Statistics
    • Adding Non negative Least Squares regression;
    • Adding Procrustes Analysis;
    • Deprecating IAnalysis in favor of the new framelet for classification,
      regression and transformation methods;
    • Merging AForge.NET and Accord.NET Histogram classes;
    • Updating IFittingOptions to implement ICloneable;
    • Adding constructors to Independent distributions accepting a lambda function
      to initialize inner components instead of relying on cloning;
    • Adding a Classes class to provide methods that operate with categorical/label data,
      such as converting boolean, double or integer values to [0;1] or [-1; +1] indicators;
    • Adding Decide methods to unambiguously transform a distance/score value into a boolean;
    • Updating statistic distributions to implement the IRandomNumberGenerator interface, meaning
      any distribution can now be used as random number generator;
    • Adding the Metropolis-Hasting sampler to generate samples from multivariate distributions
      that do not have specialized samplers;
    • Adding named constructors for building regressions directly from coefficient vectors;
    • Updating kernels to rely in Accord.Math.IDistance instead of the previous IDistance from
      the Statistics namespace;
    • Adding Pearson's Universal Kernel, Thin Spline Plate and Hellinger kernels
      contributed by Diego Catalano;
    • Moving standard statistical measures (i.e. mean, standard deviation, variance, ...) to a
      separate Measures class;
    • Updating Mean methods to operate in the same way as Sum: if a dimension is not specified,
      the Mean will be computed across all dimensions of the matrix;
    • Updating Hidden Markov Models to use the new Tagger interfaces and base classes.
  • Genetics
    • Updating the Genetics project to use the new sample generators based on statistical
      distributions;

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Accord.NET Framework 3.0.0

@cesarsouza cesarsouza released this Aug 15, 2015 · 635 commits to master since this release

Accord.NET Framework 3.0.0 release notes

16.08.2015.

Version updates and fixes:

  • GC-70: Merge with AForge.NET.
  • GC-90: Convert unit test projects to NUnit
  • GH-114: GeneralizedBetaDistribution's calls Random with wrong parameter order
  • General
    • This release marks a milestone in the Accord.NET Framework. Starting from this
      release, the AForge.NET Framework has been incorporated directly in the project,
      meaning that we are now free to fix, maintain, transform and improve AForge.NET
      directly.
    • This release provides most of the AForge.NET namespaces unchanged. This means
      that this specific version of Accord.NET Framework can be used as drop-in
      replacement in any project currently using the AForge.NET Framework and that
      is willing to upgrade to Accord.NET sometime in the future.
    • This release is mostly a transition release to help projects using the AForge.NET
      framework make the transition to Accord.NET more easily. Further releases will be
      aimed at improving the interaction between the two codebases and streamlining the
      provided functionality.

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Accord.NET Framework 2.15

@cesarsouza cesarsouza released this May 1, 2015 · 777 commits to master since this release

Build 2.15.0.5233, released on 01.05.2014

Accord.NET Framework 2.15.0 release notes

01.05.2015.

Version updates and fixes:

  • GC-56: Reuse decision attributes in the C4.5 algorithm for decision trees;
  • GC-109: The GoldfarbIdnani optimizer does not optimize well some problems;
  • GH-24: Disentangling unit test projects and adding a LGPL-only project;
  • GH-57: Decision trees created using C4.5 depends on the sorting order;
  • GH-58: SURF detector might generate Divide By Zero exceptions;
  • GH-60: Regularization breaks LogisticRegressionAnalysis in 2.14;
  • GH-61: SVM code that worked with version 2.11 now fails to converge;
  • GH-64: Exception in KPCA when using jagged matrices;
  • GH-69: Fix K-Means deserialization between framework versions.
  • General
    • Upgrading solution to VS2013 and adding support for .NET 4.5;
    • Packaging scripts can now create NuGet symbol packages;
    • The framework can now be built using Mono.
  • Accord.Statistics
    • Correcting Circular statistics' AngularDeviation method;
    • Correcting kernel profile functions and their gradient;
    • Improving the precision of the Binomial distribution;
    • Improving sample generation for Poisson and Rayleigh distributions;
    • Updating all univariate distributions to support sample generation;
    • Making sure all probability distributions implement IFormattable;
    • Adding Generalized Beta distribution with PERT estimation;
    • Adding the von-Mises Fisher distribution for circular data;
    • Adding sample generation in Beta and Generalized Beta distributions;
    • Adding estimation using the Method-of-moments and Maximum Likelihood;
    • Adding support for weighted samples in LogisticRegressionAnalysis;
    • Adding a named constructor to create an Analysis from summary data;
    • Adding all missing Shapiro-Wilk distribution's methods;
    • Adding a common interface for radial basis function kernels;
    • Adding a new generic Gaussian kernel for creating composite kernels;
    • Adding a Windowing filter in the Statistics filters namespace;
    • Adding support for weighted samples in LogisticRegressionAnalysis;
    • Adding a named constructor to create an Analysis from summary data;
    • Adding Multinomial Logistic Regression Analysis.
  • Accord.Math
    • Updating Augmented Lagragian to detect more accurately
      when the inner optimization algorithm has diverged;
    • Adding a new Fast Fourier Transform (FFT) implementation for general
      matrices and vectors whose dimensions are not necessarily powers of 2;
    • Adding Hellinge and Levenshtein distances for generic arrays;
    • Adding jagged-matrix version of the QR and Eigenvalue decompositions.
  • Accord.MachineLearning
    • Updating tree inducing algorithms (ID3 and C4.5) se they can reuse
      decision variables multiple times when creating a decision tree;
    • Correcting Levenberg-Marquardt's chain-rule Jacobian calculation
      when there are many output neurons in the learned neural network;
    • Updating the way SVM learning algorithms detect whether a machine is linear or not;
    • Updating SVM learning algorithms to use an heuristic value for
      C by default unless it has been manually specified by the user;
    • Updating the linear kernels so they are created without a constant term by default;
    • Improving multi-class SVM to generate more user-friendly stack traces when
      an exception occurs during the learning of one of the binary sub-problems;
    • Updating Kd-Trees to use interval heaps instead of general .NET structures;
    • Adding Nu-SVMs based on LibSVM's quadratic programming solver.
  • Accord.Neuro
    • Updating Levenberg-Marquardt to avoid setting lambda to zero.
  • Accord.Imaging
    • Updating IntegralImage to work with In64 matrices to avoid overflows;
    • Correcting Variance, Sauvola and Niblack threshold filters;
    • Adding Fast Variance, Wolf-Joulion Threshold, RG Chromaticity and
      Objective fidelity filters.
  • Accord.IO
    • Integrating and repackaging Sebastien Lorion's Fast CSV Reader into the Accord.IO
      namespace with an added support for auto-detecting the file's field delimiter.
  • Accord.Audio
    • Adding IWindow apply overloads to operate directly on double[] vectors;
    • Adding Sine and Custom signal generators and correcting existing ones.
  • Sample applications
    • Adding feature selection sample application using L1-regularized logistic SVMs;
    • Correcting the display of all sample applications in high-DPI displays.

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Accord.NET Framework 2.14

@cesarsouza cesarsouza released this Dec 8, 2014 · 949 commits to master since this release

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.

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Accord.NET Framework v2.13

@cesarsouza cesarsouza released this Aug 29, 2014 · 1089 commits to master since this release

Build 2.13.1.4986, released on 30.08.2014

Version updates and fixes:

  • GC-61: GoldfarbIdnani should implement the IOptimizationMethod interface;
  • GC-63: Updating optimization methods to avoid throwing exceptions;
  • GC-80: Audio.Formats.WaveDecoder.AverageBitsPerSecond should be bytes, not bits;
  • GC-85: Tools.Random is not thread safe;
  • GC-87: Add a base distance method for kernel functions;
  • GC-88: General Discrete Distribution estimation doesn't handle negative values;
  • GC-90: EmpiricalDistribution's SmoothingRule should use +0.2 in the factor calculation;
  • GC-91: Update L-BFGS optimization algorithms from the latest Fortran source algorithms;
  • GC-96: ConvexHullDefects doesn't accounts for defects between the last and first points;
  • GC-98: Fixing ProbabilityDensityFunction in MultivariateNormalDistribution;
  • GC-99: Combinatorics.Permutations(array) method does not include the original array;
  • GC-101: Issue with Haar transform at orders grater than one;
  • GH-4: Replacing SlimDX with SharpDX in Audio libraries;
  • GH-5: ComplexSignalConstructor unit test fails;
  • GH-7: Fixing typos in Haralick algorithm;
  • GH-8: Updating IntegralImage2 to support Format32bppRgb images;
  • GH-9: Binomial probability mass function result differs from Excel result;
  • GH-10: Fixing issue in Singular value decomposition clone method;
  • GH-11: Fixing issue in Statistics.Filters.Codification.Translate method;
  • GH-12: Add a HistogramBox viewer in the same spirit as ScatterplotBox and DataGridBox;
  • GH-13: NaiveBayes constructor incorrectly checks its arguments;
  • GH-25: SauvolaThreshold and NiblackThreshold filter are always making whole black image;
  • GH-27: Fixing Bernoulli distribution sampling.
  • General
    • This release brings some big changes. The SlimDX libraries have been replaced by SharpDX,
      which now enables the framework to be run into more platforms. Two new assemblies have also
      been created to further accommodate future framework extensions, such as a dedicate matrix
      format library, and an additional library for math algorithms that are not available under
      the LGPL. As such, the former Accord.Statistics.Formats namespace has been moved into the
      new Accord.IO, and a new Accord.Math.NonCommercial assembly has been created to contain
      other algorithms that are free but are not shared under a free software license and thus
      cannot be used in commercial applications.
  • Accord.IO
    • Adding a LibSVM's file model to load and save LibSVM's classifiers;
    • Adding a IDX file reader to read the MNIST (and possibly others) datasets;
    • Adding a MAT file reader to read Matlab/Octave data, including sparse,
      structures and objects.
  • Accord.Statistics
    • Fixing Codification filter when columns have a max-length constraint;
    • Fixing MultivariateNormalDistribution to handle edge cases;
    • Fixing distance computations for most kernel functions;
    • Updating Hidden Markov Model classes with more Debug assertions;
    • Updating descriptive analysis to support quantile computation;
    • Adding Deviance measure in the DescriptiveAnalysis;
    • Adding a IReverseDistance interface to separate distinct kernel distances;
    • Adding support for directly processing matrices in the Normalization filter;
    • Adding support for explicit feature space transformation in some kernels;
    • Adding Beta and Pareto distribution fitting;
    • Adding explicit Gaussian kernel projection using a Taylor approximation;
    • Adding Birnbaum-Saunders, Generalized Normal, Gumbel, Power Lognormal,
      Power Normal, Triangular, Tukey Lambda, Logistic, Hyperbolic Secant,
      Degenerate and General Continuous distributions.
  • Accord.Imaging
    • Adding new user-contributed imaging filters: Difference of
      Gaussians, HighBoost, Niblack Threshold, Sauvola Threshold.
  • Accord.Math
    • Introducing the Accord.Math.Integration namespace for numerical integration;
    • Updating FiniteDifferences to support any order and number of interpolation points;
    • Fixing NonnegativeFactorization when smaller rank approximations are requested;
    • Updating the previous L-BFGS implementation from the latest Lbfgsb.3.0 version;
    • Adding the L-BFGS optimizer with support for Orthant-Wise optimizer from LibBFGS;
    • Adding the Cobyla method for derivative-free optimization (user contribution);
    • Adding Carl Edward Rasmussen's FminCG conjugate gradient minimizer (user contribution);
    • Adding the Discrete Curve Evolution algorithm (user contribution);
    • Adding a Singular value decomposition implementation for Jagged matrices;
    • Adding a simple 2D Kalman filter implementation (user contribution);
    • Adding an 'online' version of the TruthTable method which can generate samples on the fly
      through IEnumerable. Now it can also work with any number of symbols per element position.
  • Accord.Audio
    • Fixing position calculation when sampleIndex is set in WindowBase.Apply method.
  • Accord.MachineLearning
    • Fixing SequentialMinimalOptimization when working with weighted samples;
    • Renaming ProbabilisticOutputLearning to ProbabilisticOutputCalibration;
    • Updating cross-validation to support class-balanced partitions;
    • Adding support for different sample weights in SMO and and IRLS;
    • Adding a configurable model threshold for AdaBoost learning;
    • Adding a generic base model for AdaBoost's weak classifiers;
    • Adding specialized linear SVM algorithms based on liblinear's offerings,
      such as L2-regularized L1 and L2-loss SVM for the dual formulation and
      the L2-regularized, L2-loss SVM for the primal formulation, as well as
      probabilistic SVM and Logistic Regression algorithms.
  • Accord.Controls
    • Adding HistogramBox for displaying histograms in the same manner as MessageBox;
    • Updating Scatterplot to allow for constructing a plot from a single parameter.

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Accord.NET Framework v2.12

@cesarsouza cesarsouza released this Jan 5, 2014 · 1269 commits to master since this release

Build 2.12.0.4750, released on 04.01.2014

Version updates and fixes:

  • GC-83: Error in Accord.Statistics.Tools;
  • GC-81: Redundant condition check in specialized Inverse method;
  • GC-82: Serializable annotation is needed on class contrast functions;
  • GC-66: Adding fitting options for empirical distributions.
  • General
    • The general focus for this release was again to improve
      the documentation and provide standard bug-fixing;
    • The project now also provides Debug binaries which be used
      to provide more detailed information when debugging applications.
  • Accord.Controls
    • Adding a WavechartBox control to display wavecharts with ease, in
      the same way as MessageBox can display text messages on screen.
  • Accord.Audio
    • Correcting WaveDecoder.AverageBytesPerSecond (Google Code #80);
    • Correcting the creation of base audio windows;
    • Adding the ExtractChannel filter for extracting single channels
      from multiple-channel audio signals.
  • Accord.Statistics
    • Adding generic base classes for probability distributions;
    • Adding support for computing the cumulative multivariate normal
      distribution function for specifically one and two dimensions;
    • Correcting behavior of the Binomial test under .NET 4.5;
    • Updating DescriptiveAnalysis to provide sums and confidence intervals;
    • Updating ChiSquareTest to accept ConfusionMatrices as input;
    • Unifying Univariate and Multivariate mixture distribution fitting
      through Expectation-Maximization into a single and generic class;
    • Updating the WeightedMean method to accept unnormalized weights;
    • Updating the Codification filter to work without DataTables;
    • Adding fitting options for empirical distributions (Google Code #66);
    • Adding options to robustly fit Multivariate Normal Distributions using
      the Singular Value Decomposition, avoiding non-positive definite issues.
  • Accord.MachineLearning
    • GaussianMixtureModel now accepts a maximum number of iterations;
    • Updating the KDTree class to provide a non-generic version when there
      is no interest in the kind of values stored as information in the nodes;
    • Adding specialized methods for when only the closest neighbor is needed
      in a KDTree. Also adding options to provide only an approximate answer;
    • Updating the K-Means algorithm to fully support parallel processing;
    • Adding support for generating decision rules from Decision Trees.
  • Accord.Math
    • Correcting InsertColumn and InsertRow implementations;
    • Improving Submatrix creation to avoid extra memory allocations when desired;
    • Reshape method for jagged arrays can now work with non-rectangular arrays;
    • Correcting relative convergence issues with negative watched interest values;
    • Adding Modulo and Modular distance for double-precision floating point inputs.
  • AForge Compatibility
    • Compiled against AForge.NET Framework 2.2.5. May work with newer versions.

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Accord.NET Framework v2.11

@cesarsouza cesarsouza released this Oct 27, 2013 · 1328 commits to master since this release

Build 2.11.0.4665, released on 27.10.2013

Version updates and fixes:

  • General
    • The general focus for this release was to improve the documentation,
      re-organize the sample applications and provide standard bug-fixing.
  • Accord.Controls
    • Fixing ArrayDataView to show jagged arrays in DataGridViews;
    • Adding a ComponentView control to display analysis information.
  • Accord.Imaging
    • Adding a Save overload to BagOfVisualWords (Google Code #74);
    • Marking FAST and FREAK as Serializable (Google Code #75).
  • Accord.Statistics
    • Improving documentation for the 'unbiased' parameter (Google Code #66);
    • Removing the DEBUG flag from the Statistics assembly (Google Code #78);
    • Adding NonlinearRegression models and least-squares learning algorithms;
    • Adding a option to force the use of SVD when fitting linear regressions;
    • Adding a option to disable normalization when creating Cox's models;
    • Adding MultipleBaumWelchLearning to test random weight initializations;
    • Updating HCRF learning algorithms to use relative convergence by default.
  • Accord.MachineLearning
    • Correcting the score generation on k-NN classifier (Google Code #68);
    • Fixing the Compact property of the SequentialMinimalOptimization class;
    • Correcting the KD-Tree implementation to correctly identify all neighbor
      points when querying for a finite number of neighbors (Google Code #71).
  • Accord.Math
    • Adding the Gauss-Newton and Levenberg-Marquardt Least-Squares algorithms;
    • Updating Absolute and Relative Convergence to implement a common interface;
    • Adding a configurable minimum convergence checks in relative convergence.
  • Sample applications
    • Reorganizing all sample applications, adding more relevant information
      to their description and improving their documentation.
  • AForge Compatibility
    • Compiled against AForge.NET Framework 2.2.5. May work with newer versions.

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Accord.NET Framework v2.10

@cesarsouza cesarsouza released this Sep 7, 2013 · 1359 commits to master since this release

Build 2.10.0.4632, released on 07.09.2013

Version updates and fixes:

  • General
    • This release aimed to provide improvements to the documentation.
      Most of the Univariate Distributions now include proper examples
      for all main functions and measures in their summary page.
  • Accord.Imaging
    • Adding Haralick's set of textural features;
    • Adding Local Binary Pattern (LBP) features;
    • Adding Gabor, Variance and Kuwahara filters;
    • Adding Gray-World, WhitePatch filters;
    • Adding Kirsch and Robinson edge detectors;
    • Adding Gray-Level Co-occurrence Matrices (GLCM);
    • Adding Gray-Level Run-length Matrices (GLRLM);
    • Adding Gray-Level Difference Method (GLDM);
    • Adding byte and color conversions in the ArrayToImage converter;
    • Updating IFeaturePoint's to include better conversion operators.
  • Accord.Statistics
    • Adding random Covariance matrix generation methods;
    • Adding Von-Mises cumulative distribution function;
    • Adding Poisson inverse cumulative distribution function;
    • Adding Support information for all distributions;
    • Adding support for threshold models in Markov running filters;
    • Adding default support computing the true Median and Quantile
      functions (inverse cumulative distribution function) for all
      univariate continuous distributions;
    • Improving ToString methods for linear/polynomial regressions;
    • Updating all regression methods to use SVD by default;
    • Correcting Wishart and Inverse Wishart distributions.
  • Accord.MachineLearning
    • Adding simple Minimum (Mean) Distance Classifier;
    • Adding RANSAC methods for plane, circle and line fitting;
    • Adding options to trade speed vs. accuracy in Mean-Shift;
    • Updating Bag-of-Words to support any feature point type;
    • Fixing Grid-Search issue when one of the models returns NaN;
    • Fixing issue when k-Nearest Neighbors Matching is called
      with less than k points on its second argument;
    • Improving the performance of KD-Trees and Mean Shift;
    • Updating Gaussian Mixture Model methods to report the
      classification strength (score) as an out parameter.
  • Accord.Math
    • Adding the first version of the Math.Kinematics
      namespace with Denavit-Hartenberg joint models;
    • Adding Binary Search root finding algorithm;
    • Adding missing Gamma.Inverse special function;
    • Adding Mixture Distribution's Distribution functions;
    • Adding dedicated class for Gram-Schmidt Orthogonalization;
    • Adding general purpose Resilient Backpropagation algorithm;
    • Fixing precision-loss issue in the Augmented Lagrangian Solver;
    • Updating FiniteDifferences to support configurable step sizes;
    • Updating Matrix.Range methods to require a dimension parameter;
    • Moving matrix formatters from Accord.Math.Formats to
      Accord.Math in order to improve their discoverability.
  • Accord.Vision
    • Moving the GroupMatching algorithms to Accord.Vision.
  • Sample applications
    • Adding sample application for Denavit-Hartenberg joint models;
    • Adding sample application for Eigenfaces, PCA for images;
    • Adding sample application for mouse gesture classification
      using Dynamic Time Warping Kernel Support Vector Machines.

Downloads