0.3.1
    o more extensive package description
0.3.0
    o roxygen2 documentation, check imports for submission to CRAN
0.2-2
    o fix startup message
    o better data compression
0.2-1
    o fix storing of results in classify_bioc_2.3
0.2-0
    o fix nlcv issue with limma feature selection
0.1-99
    o small documentation and namespace fixes
0.1-98
    o fix ordering by geneID in nlcv with limma feature selection
0.1-97
    o small fixes related to removal of nlcv as a4 dependency, a.o. introduction
      of dependency on a4Core
0.1-96
    o add y axis label to scores plot and improve main title
0.1-95
    o further fix of layout in mcrPlot
0.1-94
    o fix layout in mcrPlot
0.1-93
    o fix layout in scoresPlot
0.1-92
    o add randomForest explicitly to dependencies
    o fix bug in nlcv with limma feature selection, where incidentally 
      the geneID column could be a factor and therefore cause erroneous
      extraction from an ExpressionSet
0.1-91
    o rename topFeatures into topTable and turn the topFeatures function
      into a method (for 'nlcv' objects)
    o make use of sample names as x-axis labels of scoresPlot
0.1-90
	o document nldaI
0.1-89
	o confusionMatrix name space fix
0.1-88
    o replace MLearn interface for randomForest feature selection by
      plain use of the randomForest function 
0.1-87
    o add geneID argument to nlcv to allow for different gene ID names
      in the fData of the expression set
0.1-86
    o small fix for topTable in limma2Groups (which is introduced as alias for limmaTwoGroups)
0.1-85
    o turned confusionMatrix into a generic function
0.1-84
    o added sampling strategy for unbalanced class distributions; argument 'distclass' of
      functions inTrainingSample and nlcv 
0.1-83
	o fix too protective check in nlcv (randomForest feature selection)
0.1-82
	o fix to prevent pamr to mess up error handling
0.1-81
    o add fsMethod = "none"
    o add AUC for models with continuous outputs (nlda, glm)
    o store ROC curves (ROCR package)
    o add nldaI interface allowing to store testScores (for lda models)
    o add customization of ntree and mtry for feature selection using
      randomForest
    o check that mtry <= maximum of nFeatures 
0.1-80
	o regenerate example data sets
	o add check on tech in scoresPlot
0.1-79
    o small tweak to scoresPlot
    o add qda (quadratic discriminant analysis) and glm (logistic regression)
      interfaces
0.1-78
    o add rescale argument to mcrPlot function
    o add plain lda and ksvm classifiers
0.1-77
    o quick extension of pamrML and predict.pamrML for ExpressionSet objects
    o added method argument to topFeatures; can be one of "percentage",
      "meanrank" or "medianrank"
	o fix limma feature selection (use training set, not full set)
	o added inst/generateData.R, a script used to generate the data 
	  in data/
0.1-76
	o integrate pamr as an MLearn interface
0.1-75
    o remove featureSelectionRF wrapper and move code into nlcv function
    o fix randomForest feature selection code
0.1-74
	o add check on feature selection methods
	o add check on fact that it should be a two-class problem
	o new argument classifMethods to select the appropriate
	  classification methods
	o updates related to BioC 2.3 release (testPredictions 
	  instead of predLabels)
0.1-73
	o nlcv again separate package (after temporary merge with a4)
0.1-72
	o added feature selection by limma (implying an additional dependency on a4)
	o improved passing of further parameters to the feature selection method
	  (argument fsPar)
0.1-71
	o integration of final package vignette
	o xtable method for summary.mcrPlot objects added
0.1-70
	o another rewrite of simulateData
	o artificial datasets changed accordingly
0.1-69
	o artificial datasets updated (using updated nlcv)
	o fixed buglet in simulateData
0.1-68
	o fixed bug in nlcv (testPredictions returned factor, whereas 
	  predLabels returned a character vector)
	o small fix in simulateData
	o added run-time tests directory
0.1-67
	o added simulated datasets: nlcvRF, nlcvTT_SS, 
	  nlcvRF_WS, nlcvTT_WS, nlcvRF_WHS, nlcvTT_WHS, 
	  nlcvRF_R and nlcvTT_R	
	o scoresPlot: added layout argument (in order
	  to allow multiple plots on one panel)
	o rankDistributionPlot added 
0.1-66
	o scoresPlot: put information on classification technique and
	  number of features into main (instead of sub) in order to avoid
	  overlap with the sample names (x axis labels)
	o topFeatures: the percentages now represent presence in the top n,
	  instead of presence in the top 2*n
0.1-65
	o fixed simulateData (for nNoEffectCols == 0)
	o added layout argument to mcrPlot function (in order
	  to allow multiple plots on one panel)
0.1-64
	o added xtable method for confusionMatrix objects
	o added explicit dependencies to sma, ipred, pamr and xtable
0.1-63
	o featureSelectionRF added to name space
	o fixed naming issue in nlcv (featureSelectionRF instead of 
	  variableSelectionRF)
0.1-62
	o license information formatted according to rules: GPL (>=2)
	o recursiveRandomForestFS removed and replaced by featureSelectionRF;
	    the nFeaturesFinal argument of the former function has been dropped
	    accordingly in the latter function
	o simulateData gained additional arguments betweenClassDifference 
	    and withinClassSd
0.1-61
	added function simulateData 
0.1-60
	added print method for confusionMatrix objects
0.1-59
	confusionMatrix function added
0.1-58
	mcrPlot and scoresPlot gain an argument plot (defaults to TRUE)
	to allow use of the functions for computational purposes
0.1-57
	export topFeatures in NAMESPACE
0.1-56
	o scoresPlot: added supplementary legend for plot characters used
	o scoresPlot: added explicit main and sub arguments
0.1-55
	scoresPlot: draw grid first, then add dots
0.1-54
	scoresPlot: vectorize drawing of class membership strip
0.1-53
	scoresPlot: fix drawing of class membership strip
0.1-52
	added dependency on RColorBrewer for class membership display
	on scoresPlot
0.1-51
	added topFeatures function and help page
0.1-50
	put legend for scoresPlot in comment
0.1-49 
	make use of testPredictions instead of predLabels
	(new version of MLInterfaces)
0.1-47
	remove remnant "type"s and replace with the appropriate
	variable passed as arguments to the functions (classVar argument)
0.1-46
	replace randomForestB by MLearn and the appropriate method
0.1-45
	removed warnings from generateData (by making a
	real ExpressionSet)
