Tags give the ability to mark specific points in history as being important
  • 1.7.5   version 1.7.5
    Release 1.7.5
    • New: A Makefile for mingw to build on Windows.
    • Changed: PR #94 added a much more efficient sparse kernel.
    • Changed: boilerplate code for Julia greatly improved.
    • Changed: Code cleanup, pre-processor macros simplified.
    • Changed: Adapted to Seaborn API changes in plotting heatmaps.
  • 1.7.5-pre
    c3a02b7d · Need for -DCLI removed ·
  • 1.7.4   version 1.7.4
    c5aab401 · Typos fixed ·
    Release 1.7.4
    • Fixed: The random seed was set to 0 for testing purposes. This is now changed to a wall-time based initialization.
  • 1.7.3   version 1.7.3
    6068f861 · Changelog updated ·
    Release 1.7.3
    • New: Verbosity parameter in the command-line, Python, MATLAB, and Julia interfaces.
    • Changed: Calculation of U-matrix parallelized.
    • Changed: Moved feeding data to train method in the Python interface.
    • Fixed: Sparse matrix reader made more robust.
    • Fixed: Compatibility with kohonen 3 resolved.
    • Fixed: Compatibility with Matplotlib 2 resolved.
  • 1.7.2   version 1.7.2
    Release 1.7.2
    • New: The coefficient of the Gaussian neighborhood function exp(-||x-y||^2/(2*(coeff*radius)^2)) is now exposed in all interfaces as a parameter.
    • New: get_bmu function in the Python interface to get the best matching units given an activation map.
    • Changed: Updated PCA initialization in the Python interface to work with sk-learn 0.18 onwards.
    • Changed: Radii can be float values.
    • Fixed: Only positive values were written back to codebook during update.
    • Fixed: Sparse data is read correctly when there are class labels.
  • 1.7.1   version 1.7.1
    Release 1.7.1
    • Fixed: macOS build works again.
  • 1.7.0   version 1.7.0
    Release 1.7.0
    • New: Julia interface is available (https://github.com/peterwittek/Somoclu.jl).
    • New: Method get_surface_state of the Somoclu object in Python calculates the activation map for all data instances.
    • New: Method view_activation_map of the Somoclu object in Python allows plotting the activation map for the training data instances or for a new data instance.
    • New: Method view_similarity_matrix of the Somoclu object in Python visualizes the similarity matrix of data points according to their distance to the nodes in the map.
    • Fixed: CRAN-friendliness improved.
  • 1.6.2   version 1.6.2
    Release 1.6.2
    • Changed: In-place codebook updates when compiled without MPI. This improves update speed and substantially cuts memory use.
    • Changed: Compatible with Visual Studio 15.
    • Fixed: The BMUs returned after training were from before the last epoch. Now another round of BMU search is done.
    • Fixed: Training can continue on the same data in the Python wrapper.
    • Fixed: GPU memory allocation problem on Windows.
  • 1.6.1   version 1.6.1
    Release 1.6.1
    • New: Option for PCA initialization is added to the Python interface.
    • New: Clustering of the codebook with arbitrary clustering algorithm in scikit-learn is now possible in the Python interface.
  • 1.6   version 1.6
    ec2a9d3f · Release date updated ·
    Release 1.6
    • New: R wrapper integrates with kohonen package.
    • New: MATLAB wrapper integrates with soomtoolbox.
    • New: Better handling of CUDA compilation in the Python interface.
    • Changed: Throws an exception if GPU kernel is requested, but it was compiled without it. The earlier behaviour quietly defaulted to the CPU kernel.
  • 1.5.1   version 1.5.1
    Release 1.5.1
    • New: Neighborhood function can be chosen between Gaussian and bubble.
    • Fixed: R wrapper passes arrays with correct orientation.
    • Fixed: io.cpp is no longer required in the wrappers. An exception is thrown when needed.
  • 1.5
    Release 1.5
    • New: Python interface has visual capabilities.
    • New: Option for hexagonal grid.
    • New: Option for requesting compact support in updating the map.
    • New: Python, R, and MATLAB interfaces now allow passing an initial codebook.
    • Changed: Reduced memory use in calculating U-matrices.
    • Changed: Build system rebuilt and simplified.
  • 1.4.1   version 1.4.1
    451705df · Documentation updated ·
    Release 1.4.1
    • Better support for ICC.
    • Faster code when compiling with GCC.
    • Building instructions and documentation improved.
    • Bug fixes: portability for R, using native R random number generator.
  • 1.4   version 1.4
    c5ba668a · Preparing for release 1.4 ·
  • 1.3.1   version 1.3.1
    9cfbb6fe · R version cleaned up ·
  • 1.3   version 1.3
    9a8dd65b · Documentation updated ·
  • 1.2   version 1.2
    9500571f · Version 1.2 ·
  • 1.1.2   version 1.1.2
    7ea3872a · Documentation updated ·
  • 1.1.1   version 1.1.1
    7ea3872a · Documentation updated ·
  • 1.1   version 1.1