Release Notes Version 9 0

Changes and Bug Fixes in Version 9.0

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

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

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 an axisscale from selected points in a plot of X-block data via context (right-click) menu. Use this with the changes to Create Y from X-block Axis Scale to quickly create a Y-block.
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).

File	Comment
analysis	Can now create Y-block from X-block column, axisscale, or class set. And where appropriate, can choose to delete selection from X-block or exclude.
constrainfit	Add 'exponential' to type of constraints available.
experimentreadr	When splitting data into Cal/Val can now keep replicates based on class set from X or Y block. Also can choose to Mahalanobis distance or Euclidean distance.