CHANGES

VERSION 0.0.7 (2021-03-29)
	- added MetaCost methods for classification and regression (based on MeatCost from Domingos, 1999)
	- added methods for introducing a Neighbourhood Bias in smoteR and under-sampling for regression and classification
	- added SMOGN algorithm for imbalanced regression
	- added MetaUtilRegress algorithm
	- added bagging method for dealing with imbalanced regression problems
	- improvements of functions documentation 
	- bugs correction in HVDM function (thanks to Miriam Santos and Arne Camps for noticing this)
	- correction added in ADASYN function to solve examples generation when there are no nearest neighbours in the baseClass

VERSION 0.0.6 (2017-06-20)
	- added adasyn algorithm for classification
	- added method for interpolating utility/benefit/cost surfaces
	- added utility-based metrics for classification and regression tasks (utility, cost and benefit)
	- added a function for utility-based learning optimization for classification (from Elkan 2001)
	- added a function for utility-based learning optimization for regression
	- added a function that returns the distances between all pairs of 
          example computed according to a selected distance metric
	- bugs correction in SmoteRegress function (caused by constant features)
	- bugs correction on RandOverClassif (caused by classes with only one example)
	- bugs correction on neighbours function (Fortran code)
	- routines registration added

VERSION 0.0.5 (2016-07-13)
	- added two synthetic data sets, for classification and regression
	- correction of bugs
	- added verifications of percentages provided for under/over-sampling that should be less/greater than 1 in each case.
	- improvements of functions documentation
	- improved warnings issued when no change is performed in the data set
	- vignettes restructured to use the synthetic data sets introduced in this version

VERSION 0.0.4 (2016-04-28)
	- correction of bugs related with FORTRAN code

VERSION 0.0.3 (2016-04-15)
	- first version