Release Notes Version 5 8: Difference between revisions

From Eigenvector Research Documentation Wiki
Jump to navigation Jump to search
imported>Scott
(Created page with '==NEW FEATURES== ===Model Building=== * SVM * LWR ===Scores Plots=== * KNN Score Distance metric available in scores plots of PLS, PCR, and PCA (knnscoredistance). * Improv…')
 
imported>Jeremy
No edit summary
 
(13 intermediate revisions by 2 users not shown)
Line 1: Line 1:
Version 5.8 of PLS_Toolbox and Solo was released in February, 2010.
For general product information, see [http://www.eigenvector.com/software/pls_toolbox.htm PLS_Toolbox Product Page]. For information on Solo, see [http://www.eigenvector.com/software/solo.htm Solo Product Page].
(back to [[Release Notes PLS Toolbox and Solo]])
==NEW FEATURES==
==NEW FEATURES==
===Compatibility===
* Updated for Matlab 2010a compatibility.


===Model Building===
===Model Building===
* SVM
* Support Vector Machine Regression and Classification non-linear modeling methods available in Analysis GUI (Solo and PLS_Toolbox) and command-line (PLS_Toolbox).
* LWR
* Locally Weighted Regression (LWR) non-linear modeling method available in Analysis GUI and significantly revised at the command-line to add new features, preprocessing support, and compatibility with Solo_Predictor 2.1
* Permutation test added to Analysis GUI to allow easy testing for over-fit regression models (randomized y-block).
* TrendTool outputs model structures which can be used to make predictions on new data and are compatible with Solo_Predictor 2.1. Interface is also now accessible through [[EVRIGUI_Objects]]
* PLS-DA prior probability settings now available in Analysis GUI.


===Scores Plots===
===Scores Plots===
* KNN Score Distance metric available in scores plots of PLS, PCR, and PCA ([[knnscoredistance]]).
* Prediction intervals (Estimated prediction error) accessible in Scores plots
* Improved handling of class modifications.


===Preprocessing===
===Preprocessing===
* Kaiser Optical Systems HoloReact method importer to create preprocessing from band-area methods ([[hrmethodreadr]]).
* Add "Transmission to Absorbance" preprocessing method (-log10(T)).
* GLSW/EPO: add "meancenter" option to better handle orthogonalization to specific clutter matrix, plus improved help ([[glsw]]).
* Improved memory and speed performance for various preprocessing methods.
* Custom [[SpectraQuant_Filtering| SpectraQuant Filtering algorithm]] for background correction (available only through Hamilton Sundstrand)


===Importers/Exporters===
===Importers/Exporters===
* Experiment File Importer - reads file containing filenames and reference measurement data and imports the corresponding files and data into Analysis GUI. Automatically assigns the data to X and Y and to calibration and validation blocks ([[experimentreadr]]).
* Analytical Spectral Devices (ASD) Indico (Versions 6 and 7) data file reader added.
* Hamilton Sundstrand PIONIR PDF file importing added ([[pdfreadr]]).
* Horiba JY file importer fixes to data type handling and converts all data to double precision when importing.
* Horiba JY file importer performance and support for large files improved ([[hjyreadr]]).
* Fix Excel reader problem which makes some XLS files unreadable on 64-bit systems.
* SPC file importer reads file comments ([[spcreadr]]).
* Support for combining multiple DataSets. Selecting multiple items in Workspace Browser provides access to new "combine" menu option.
* XY file importing performance improved ([[xyreadr]]).
* XML importing/exporting support and performance improved ([[parsexml]] / [[encodexml]]).
* Improved support for manual parsing of CSV files ([[xclreadr]]).
* Export Data to Analect Spectral Files (ASF) ([[writeasf]]).
* Export Data to simple CSV file format for non-DataSet objects ([[writecsv]]).
* Export regression Models to CPSA32/PC80 .tbl format  (available only through Hamilton Sundstrand).


===Other Enhancements===  
===Other Enhancements===  
* Plot Controls: Full access to all items in a DataSet (no longer limited by number of rows or columns)
* Demo datasets now easily available in Model Cache.
* BoxPlot: new box plot function (PLS_Toolbox only) to allow better coexistance with Statistics Toolbox (R) from The Mathworks ([[boxplot]])
* Clearer deliniation of method categories and access to help in Analysis GUI.
* Toolbars: Toolbars are now present on most interfaces and plots to make standard actions and interaction between GUIs easier.
* Improved appearance and Copy/Paste functionality for MAC and Linux platforms.
* TrendTool: Improved interactivity and functionality.
* NND Score Distance calculation now uses Mahalanobis distance
* Model Cache: Improved performance and support for new information in models and DataSets.
* Improved Copy/Paste functionality from DataSet Editor data table (labels included and formatted for Excel compatibility)
* InfoBox: New File/Save menu option.
* Improved "single-window" feature - have all PLS_Toolbox or Solo windows "docked" in a single frame.
* DataSet Object: Add ability to log user comments to history.
* DataSet Object: Add uniqueID field and support.


==NEW FUNCTIONS AND FILES==
==NEW FUNCTIONS AND FILES==


:[[asdreadr]] - Imports data from Analytical Spectral Devices (ASD) Indico (Versions 6 and 7) data files.
:[[asdreadr]] - Imports data from Analytical Spectral Devices (ASD) Indico (Versions 6 and 7) data files.
:[[clipboard_image]] - Copy and paste images to/from the system clipboard.
:[[ismodel]] - Returns boolean TRUE if input object is a standard model structure.
:[[lwr]] - Locally Weighted Regression (LWR).
:[[svm]] - Support Vector Machine (LIBSVM) for regression or classification.
:[[svmda]] - Support Vector Machine (LIBSVM) for classification.

Latest revision as of 08:54, 26 August 2010

Version 5.8 of PLS_Toolbox and Solo was released in February, 2010.

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

Compatibility

  • Updated for Matlab 2010a compatibility.

Model Building

  • Support Vector Machine Regression and Classification non-linear modeling methods available in Analysis GUI (Solo and PLS_Toolbox) and command-line (PLS_Toolbox).
  • Locally Weighted Regression (LWR) non-linear modeling method available in Analysis GUI and significantly revised at the command-line to add new features, preprocessing support, and compatibility with Solo_Predictor 2.1
  • Permutation test added to Analysis GUI to allow easy testing for over-fit regression models (randomized y-block).
  • TrendTool outputs model structures which can be used to make predictions on new data and are compatible with Solo_Predictor 2.1. Interface is also now accessible through EVRIGUI_Objects
  • PLS-DA prior probability settings now available in Analysis GUI.

Scores Plots

  • Prediction intervals (Estimated prediction error) accessible in Scores plots

Preprocessing

  • Add "Transmission to Absorbance" preprocessing method (-log10(T)).

Importers/Exporters

  • Analytical Spectral Devices (ASD) Indico (Versions 6 and 7) data file reader added.
  • Horiba JY file importer fixes to data type handling and converts all data to double precision when importing.
  • Fix Excel reader problem which makes some XLS files unreadable on 64-bit systems.

Other Enhancements

  • Demo datasets now easily available in Model Cache.
  • Clearer deliniation of method categories and access to help in Analysis GUI.
  • Improved appearance and Copy/Paste functionality for MAC and Linux platforms.
  • NND Score Distance calculation now uses Mahalanobis distance
  • Improved Copy/Paste functionality from DataSet Editor data table (labels included and formatted for Excel compatibility)
  • Improved "single-window" feature - have all PLS_Toolbox or Solo windows "docked" in a single frame.

NEW FUNCTIONS AND FILES

asdreadr - Imports data from Analytical Spectral Devices (ASD) Indico (Versions 6 and 7) data files.
clipboard_image - Copy and paste images to/from the system clipboard.
ismodel - Returns boolean TRUE if input object is a standard model structure.
lwr - Locally Weighted Regression (LWR).
svm - Support Vector Machine (LIBSVM) for regression or classification.
svmda - Support Vector Machine (LIBSVM) for classification.