Release History
The table below lists the improvements and bug fixes of the last DataLab versions. The latest release can
be loaded from the download page. Please note that updates which are not yet part of the last major release can be activated by using the automatic update mechanism (see also the list of the latest changes).
Release 4.000 [2021-02-05] |
New Features
- DLabPascal now provides an integrated debugger
- several extensions of the built-in DLabPascal library
- signal integration tool
- a tool for calculating binary classifier metrics
- new statistical test: median test
Improvements and Changes
- Wilcoxon test report now displays the median of the differences as well
- redesigned random forest form
- a variable set repository makes the selection of variables much more convenient
- the RF applicator has now an option to create binary results for classifiers
- the PLS Applicator now shows the CF thresholds and allows to store the results in the aux. maxtrix or append it to the data matrix
- the data editor now supports ^C and ^V for copy and paste (instead of 'extract from clipboard')
- refurbished k-means clustering
- RBF network extended
- PLS/DA now displays more classifier metrics (same as MBL)
- numerical editor: row names are now displayed using a much longer maximal length; two additional fonts (Tahoma, Verdana) included
- MLR and Ridge Regression diagrams provide now more plot options
- memory based learner improved in many details
- refurbished Kohonen map
- improved edit/selection mode in data description window
- additional performance metrics for RF classifiers
- formula editor now uses the ° symbol as cell reference
- class color setup dialog now supports saving and loading color palettes
- the default class color palette has been improved
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Release 3.951 [2020-03-26] |
New Features
- Linear Discriminant Analysis (LDA)
- new statistical tests: chi2 goodness-of-fit, contingency analysis, adjusted Rand index
- extended DLabPascal:
- full support of the programmatic control of the plot parameters
- many extensions of the built-in library
- memory based learner (kNN) is now supported by DLabPascal
- univariate regression tool can now generate a DLabPascal script
Improvements and Changes
- user interface of the growing neural network improvd
- added a new and better language selection dialog
- the symbol used for dot attribute in 2d plots can now be selected by the user
- all save dialogs are now exhibiting a consistent user interface
- major revision of the memory based learner (kNN)
- added documentation for TAssocArray
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Release 3.910 [2019-03-29] |
New Features
- DataLab provides now an "open windows" selector which allows to switch between windows
- the data plots now provide a graphical marking tool to apply red and blue marks using either a lasso or a rectangle
- DataLab offers now a universal scripting language called DLabPascal which allows to automate recurring tasks
- the newly implemented memory based learning tool provides powerful option both for regression modelling and classification
- a new baseline correction tool allows to correct the baseline of a signal
- all windows can now be detached from the DataLab master window to allow for multiple monitors
- DataLab now supports random forest models (both regression models and classifiers)
- contingency analysis and Fisher's exact test are now available for the analysis of nominal data
Improvements and Changes
- pressing the ESC key now closes the current window (if appropriate)
- various MLR improvements: Cook's distance is now calculated and displayed as a graph; Durbin-Watson-Test now displays the critical limits and the decision
- drawn from the test; added 'copy y-hat to matrix clipboard' to the MLR results page;
- ridge regression: implemented a trace of parameter significance
- fixed zoom mode of 2D plots improved
- implemented binomal distribution in distribution calculator
- the desktop color can now be set by the user
- the digitizer accepts now PNG images as well
- extended 2D data designer: data can be loaded from main data table; two specific columns of the data matrix can be overwritten
- the plot window now has coordinate and object display
- the scaling tool now supports q-normalisation ánd squashing functions
- various improvements of the simple regression tool: data points can now be connected, polynomial coefficients are now evaluated by adding the p-values, residuals can now be plotted against the object index, plot parameters can now be adjusted
- cluster analysis: base line is now moveable to allow for long object names
- implemented the creation of mutually exclusive test and training sets in the data split tool
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Release < 3.910 |
Release history of versions before release 3.910 has been deleted for brevity |
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