- install_LUCS_KDD_CMAR() and install_LUCS_KDD_CPAR(): Added more checks. This fixes timing issues with untar.
- mineCARs now uses by default minimum LHS-support (via parameter originalSupport = FALSE).
- the CBA_ruleset function is now used consistently as the constructor for CBA objects.
- added transactionCoverage.
- added uncoveredClassExamples.
- added uncoveredMajorityClass.
- added transactions2DF to convert transactions to a data.frame.
- RCAR is now faster (does not run glmnet again for the chosen lambda) and returns the whole regularization path.
- prepareTransactions now automatically add a negative class item if needed.
- moved the experimental algorithms wCBA and bCBA to Work.
- R/Weka-based classifiers have now a default class.
- Version 1.2.0 has a major interface cleanup. This might require some change in existing code.
- The classifiers now use as the default a min. confidence of .5 and maxlen of 5 (max. rule length).
- CBA now includes a default rule in the rule base.
- added prepareTransactions to discretize and convert a data.frame into transactions.
- added response to convert class items to class labels (factors).
- added majorityClass.
- added FOIL.
- added RIPPER C4.5, and PART (via RWeka).
- added PRM, CPAR and CMAR (via LUCS-KDD Software Library).
- added datasets Mushroom and Lymphography.
- maintenance release.
- added RCAR (by Tyler Giallanza).
- The interface for CBA() was updated.
- CBA now complains if no rules are found.
- CBA has now also M1 pruning.
- mineCARs now uses ... to construct the parameters for apriori().
- discretizeDF.supervised method mdlp now produces a better error message if it fails.
- cleaned up the predict code to improve speed.
- mineCARs has now a balanced support option.
- convenience function classFrequency added.
- added new function discretizeDF.supervised for supervised discretization.
- added new convenience function mineCARs to mine class association rules.
- the formula interface now parsed the right hand side to restrict the used predictors.