Changelog
Version 0.7.2
- Added as.data.frame S3 method for transforming
SDEFSR_Dataset into a data.frame.
- Method plotRules() is changed by the default S3
plot() method for class SDEFSR_Rules.
- Changed cat() and print() message with
message() or warning() in order to be easily
removed.
- Fixed minor errors.
Version 0.7.1.0
- Change the name of the read.keel() function to
read.dataset().
- Added direct support for CSV files on read.dataset().
- Rename keel class to SDEFSR_Dataset class.
- Rename keelFromDataFrame() to
SDEFSR_DatasetFromDataFrame().
- Added a new object SDEFSR_Rules which:
- Contains all rules generated by an SD algorithm an its associated
quality measures.
- The “[]” operator supports filter rules by quality measure
- Added S3 method “sort” to sort rules by a given quality measure
- Added new method plotRules() which shows a TPR vs FPR plot
by using ggplot2 package.
- Fixed error when reading ARFF files with quoted ’’ variables.
- Changes of the UI:
- Added a new visualization method: Variable vs variable
- Added functionality to filter numerical variables
- Added functionality to filter instances by the given numeric or
categorical filters
- On quality measure tab, the functionality to show the plot of
plotRules() is displayed
- Changed the server logic to work with the new SDEFSR_Rules object to
improve performance on large results.
Version 0.7.0.0
- Added a new subgroup discovery algorithm:
FuGePSD.
- New dataset files support:
- ARFF files support from read.keel()
- Conversion from data.frame to keel with
keelFromDataFrame() function.
- Minor optimizations when reading a file.
- Some algorithm optimizations, changed a bit the way of calling the
functions Be aware with this!
- Fixed problem of the algorithms that returns four files instead of
three. Now all the algorithms (except FuGePSD) returns three files.
- Created S3 method to visualize keel objects with
print() and summarize with summary()
- Changes of the UI:
- Algorithm selection an parameters now are on the tab panel of the
right side of the UI after “Exploratory analysis”. We think with this
change the user has a better workflow and a better visualisation and
organization of the results.
- Also, the new functionality is available on the GUI, except the
conversion from data.frame.