Release Notes Version 9 0

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Changes and Bug Fixes in Version 9.0

Beta Testing

  • As of 09/17/2021 PLS_Toolbox and Solo are in pre-release.
  • Users should contact helpdesk@eigenvector.com to report bugs.
  • These notes are subject to change.

Version 9.0 of PLS_Toolbox and Solo is scheduled for released in October, 2021.

General Information

For general product information, see PLS_Toolbox Product Page. For information on Solo, see Solo Product Page.

(back to Release Notes PLS Toolbox and Solo)

New Features in Solo and PLS_Toolbox

  • Solo is now built with version 2020b of Matlab.
  • Python Integration
    • This release introduces several Python methods. In order to use these please follow the instructions to get started: Python Configuration. These steps are necessary to use the new methods. Once configured, try the following:
      • ANNDL - Artificial Neural Network Deep Learning.
      • ANNDLDA - Artificial Neural Network Deep Learning for classification.
      • UMAP - Uniform Manifold Approximation and Projection (Unsupervised).
      • TSNE - t-distributed Stochastic Neighbor Embedding.
      • For more info about PLS_Toolbox Python integration see the wiki Python.
  • PLOTGUI - Create a Y-block from selected points a plot of X-block data via context (right-click) menu.
  • KNN
    • Select Class Groups interface now available in the KNN Analysis window.
    • Add option to use compression.
  • SIMCA
    • Sub models can now use independent preprocessing and included variables from the Analysis interface.
    • Building SIMCA model from command line can now pass cell array of individual PCA models (built from the same dataset).

Other Changes

File Comment
analysis
  • When creating Y-block from column in X-block, column will be hard-deleted from X-block.
constrainfit
  • Add 'exponential' to type of constraints available.
experimentreadr
  • When doing Cal/Val split and keeping replicates, user can now select class set from X or Y block.