Release Notes Version 5 8: Difference between revisions
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Version 5.8 of PLS_Toolbox and Solo was released in February , 2010. | Version 5.8 of PLS_Toolbox and Solo was released in February, 2010. | ||
For general product information, see [http:// | 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. | * Updated for Matlab 2010a compatibility. | ||
===Model Building=== | ===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). | ||
* 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=== | ||
* | * Prediction intervals (Estimated prediction error) accessible in Scores plots | ||
===Preprocessing=== | ===Preprocessing=== | ||
* Add Transmission to Absorbance preprocessing method (-log10(T)). | * Add "Transmission to Absorbance" preprocessing method (-log10(T)). | ||
===Importers/Exporters=== | ===Importers/Exporters=== | ||
* Analytical Spectral Devices (ASD) Indico (Versions 6 and 7) data file reader added. | * Analytical Spectral Devices (ASD) Indico (Versions 6 and 7) data file reader added. | ||
* Horiba JY file importer fixes to data type handling. | * Horiba JY file importer fixes to data type handling and converts all data to double precision when importing. | ||
* Fix | * Fix Excel reader problem which makes some XLS files unreadable on 64-bit systems. | ||
===Other Enhancements=== | ===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== | ==NEW FUNCTIONS AND FILES== | ||
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:[[clipboard_image]] - Copy and paste images to/from the system clipboard. | :[[clipboard_image]] - Copy and paste images to/from the system clipboard. | ||
:[[ismodel]] - Returns boolean TRUE if input object is a standard model structure. | :[[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. | :[[svm]] - Support Vector Machine (LIBSVM) for regression or classification. | ||
:[[svmda]] - Support Vector Machine (LIBSVM) for classification. | :[[svmda]] - Support Vector Machine (LIBSVM) for classification. | ||
Latest revision as of 07:54, 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.