-------------------
Version: 3.45
Date: 2008-10-17

Added caching of RWeka objects to that they can be saved to the file system and
used in other sessions. (changes per Kurt Hornik on 2008-10-05)

-------------------
Version: 3.44
Date: 2008-10-15

Added sda from the sparseLDA pacakge (not on CRAN). 

Also, a bug was fixed where the ellipses were not passed into a few of the newer 
models (such as penalized and ppr)

-------------------
Version: 3.43
Date: 2008-10-03

Added the penalized model from the penalized package. In caret, it is regression only
although the package allows for classification via glm models. However, it does not
allow the user to pass the classes in (just an indicator matrix). Becuase of this, it
doesn't really work with the rest of the classification tools in the package.

-------------------
Version: 3.42
Date: 2008-09-26

Added a little more formatting to print.train

-------------------
Version: 3.41
Date: 2008-09-19

For gbm, let the user over-ride the default value of the distribution argument (brought
us by Peter Tait via RHelp).

-------------------
Version: 3.40
Date: 2008-09-18

Changed predict.preProcess so that it doesn't crash if newdata does not have all of the
variables used to originally pre-process *unless* PCA processing was requested.

-------------------
Version: 3.39
Date: 2008-09-18

Fixed bug in varImp.rpart when the model had only primary splits.

Minor changes to the Affy normalization code

Changed typo in predictors man page

-------------------
Version: 3.38
Date: 2008-09-09

Added a new class called predictors that returns the names of the predictors that were
used in the final model.

Also added ppr from the stats package.

Minor update to the project web page to deal with IE issues

-------------------
Version: 3.37
Date: 2008-09-04

Added the ability of train to use custom made performance functions so that the tuning
parameters can be chosen on the basis of things other than RMSE/R-squared and 
Accuracy/Kappa. Specific changes:

  - a new argument was added to trainControl called "summaryFunction" that is used
    to specify the function used to compute performance metrics. The default function
    preserves the functionality prior to this new version

   - a new argument to train is "maximize" which is a logical for whether the 
    performance measure specified in the "metric" argument to train should be 
    maximized or minimized.

   - the selection function specified in trainControl carries the maximize argument with
     it so that customized performance metrics can be used.

Other changes:

  - a bug was fixed in confusionMatrix (thanks to Gabor Grothendieck)

  - another bug was fixed related to predictions from least square SVMs 

-------------------
Version: 3.36
Date: 2008-08-29

Added superpc from the superpc package. One note: the data argument that is passed
to superpc is saved in the object that results from superpc.train. This is used later in
the prediction function.

-------------------
Version: 3.35
Date: 2008-08-27

Added slda from ipred

-------------------
Version: 3.34
Date: 2008-08-25

Fixed a few bugs related to the lattice plots from version 3.33.

Also added the ripper (aka JRip) and logistic model trees from RWeka

-------------------
Version: 3.33
Date: 2008-08-22

Added xyplot.train, densityplot.train, histogram.train and stripplot.train. These are 
all functions to plot the resampling points. There is some overlap between these
functions, plot.train and resampleHist. plot.train gives the average metrics only while 
these plot all of the resampled performance metrics. resampleHist could plot all of the 
points, but only for the final optimal set of predictors.

To use these functions, there is a new argument in trainControl called returnResamp 
which should have values "none", "final" and "all". The default is "final" to be consistent 
with previous versions, but "all" should be specified to use these new functions to their 
fullest.

-------------------
Version: 3.32
Date: 2008-07-28

The functions "predict.train" and "predict.list" were added to use as alternatives to the
extractPrediction and extractProbs functions. 

Added C4.5 (aka J48) and rules-based models (M5 prime) from RWeka.

Also added logitBoost from the caTools package. This package doesn't have a 
namespace and RWeka has a function with the same name. It was suggested to use the
"::" prefix to differentiate them (but we'll see how this works).



