Changes in Version 1.5-25

  o add auto-coercion from Matrix and simple_triplet_matrix objects 
    to predict.svm()

  o Bug fix in tune.svm: when a data frame was provided as validation sample,
    the response variable was not correctly extracted.

Changes in Version 1.5-24

  o Cosmetics: use sQuote() instead of hard-coded quotes in warnings
    and error messages in several places.

  o Bug fix in labeling of decision values

  o add decision.values of fitted values to a svm object

Changes in Version 1.5-23

  o Bug fix in svm(): Error messages returned by the C function have not been
    correctly handled, causing seg faults.

Changes in Version 1.5-22

  o minor fix

Changes in Version 1.5-21

  o Allow sparse_triplet_matrix objects for svm()

Changes in Version 1.5-20

  o More flexible interface to naiveBayes() 
  o Fix bugs in docs for kurtosis()

Changes in Version 1.5-19

  o Fix bugs in {read,write}.matrix.csr
  o Allow Matrix objects for svm()
  o Version bump of libsvm to 2.88

Changes in Version 1.5-18

  o Improve DESCRIPTION install metadata.

Changes in Version 1.5-17

  o tune() now also returns a dispersion measure of all training samples. 
    Bootstrap is done *with* replacement.

  o tune.svm now also accepts the epsilon-parameter

Changes in Version 1.5-16

  o write.svm now also stores the scaling information for the dependent 
    variable

  o data sets Glass, HouseVotes84, and Ozone removed (are in package mlbench)

  o merged help pages for naiveBayes and predict.naiveBayes


Changes in Version 1.5-15

  o Bug in NAMESPACE-file fixed (conditional import from utils failed in 
    R 2.3.1).


Changes in Version 1.5-14

  o predict.naiveBayes sped up
  o Bug fix in plot.svm (error in case of training categories without predictions)
  o methods now added to `Suggests:', and grDevices to imports


Changes in Version 1.5-13

  o Bug fix: sparse handling was broken since 1.5-9


Changes in Version 1.5-12

  o update to libsvm 2.81
  
  o laplace smoothing added to naiveBayes()

  
Changes in Version 1.5-11

  o tune: allow list of vectors as tune parameter range so that 
          class.weights in svm-models can be tuned.

  o better default color palette for plot.tune().

  o New function probplot() for probability plots.

Changes in Version 1.5-10

  o Bug fix: class probability prediction was broken since 1.5-9 

  
Changes in Version 1.5-9

  o tune() now returns the split indices into training/validation set.
    Information added about cross validation.

  o plot.svm(): wrong labeling order in levels fixed.

  o predict.svm now adds row numbers to predictions, and correctly handles 
    the na.action argument using napredict()

    
Changes in Version 1.5-8

  o Update to libsvm 2.8 (uses a faster optimization algorithm)

  
Changes in Version 1.5-7

  o read.matrix.csr() did not work correctly with matrix-only objects.

  o svm(): Fixed wrong labeling for predicted decision values and
    probabilities in case of a Class factor created from a non-ordered
    character vector.


Changes in Version 1.5-6

  o cmeans() is substantially enhanced, with a complete rewrite of the
    underlying C code.  It is now possible to specify case weights and
    the relative convergence tolerance.  For Manhattan distances, centers
    are correctly computed as suitably weighted medians (rather than
    means) of the observations.  The print method for fclust objects is
    now more in parallel with related methods, and registered in the name
    space.


Changes in Version 1.5-5

  o read.octave() is now deprecated in favor of a substantially enhanced
    version in package foreign for reading in files in Octave text data
    format. 


Changes in Version 1.5-4

  o Use lazy loading.


Changes in Version 1.5-3

  o New arguments in plot.svm for customizing plot symbols and colors

  o Fix of broken code in plot.svm for the `fill=FALSE' (non-default) case


Changes in Version 1.5-2

  o Fixed memory leak in svm

  
Changes in Version 1.5-1

  o Fixed C++ style comments

  
Changes in Version 1.5-0

  o Example for weighting added in svm() help page

  o upgrade to libsvm 2.6: support for probabilities added

  
Changes in Version 1.4-1

  o NaiveBayes() is more accurate for small probabilities

  o call is more sensible in tune(), tune.foo(), and best.foo() objects

  o `control' parameter of tune() changed to `tunecontrol' to solve 
    name space conflict with training methods using `control' themselves

  o new function matchControls()

  o fixed a bug in bclust() triggered when a cluster had only one center

  
Changes in Version 1.4-0

  o adjusted to restructering of R base packages

  o added a NAMESPACE file

  o Function `write.svm' now also creates a file with scaling 
    information  

    
Changes in Version 1.3.16:

  o Small bug fixes in predict.svm() and plot.svm()

  o Function `write.svm' added which saves models created with svm() in
    the format libsvm can read. 

    
Changes in Version 1.3.15:

  o Bug fix in plot.svm(): non-SVs had wrong colors

  o data sets `Ozone' and `Glass' added 

  
Changes in Version 1.3.14:

  o Several Docu bug fixes (plot.bclust, impute, stft, svm.formula, svm.default)

  o upgrade to libsvm 2.5. New feature: predict.svm() optionally
    returns decision values for multi-class classification

  o svm-vignette gave warnings due to rank deficiency in Ozone data

  o naiveBayes() now also supports metric predictors, and the standard
    interface.

Changes in Version 1.3.13:

  o Bug fixes in svm:
    - Prediction of 1 single observation gave an error
    - Only k instead of k*(k-1)/2 rho coefficients have been returned by svm 
      (k number of classes), having caused nonsensical results for k > 3.
  o The `svmdoc' file in inst/doc now is a vignette.

Changes in Version 1.3-12:

  o The x argument of cmeans() and bclust() is now automatically coerced
    to a matrix.

  o Started tests directory

  o New method: `naiveBayes' classifier for categorical predictors

  o optimization of `read.matrix.csr' which used to be rather slow

  o Bug fixes for the `svm' interface: when the data included
    categorical predictors, the scaling procedure did not only
    affect the metric variables, but also the binary variables
    in the model matrix.

  o Function `scaclust removed'. Bug has to be fixed. 

Changes in Version 1.3-10:

  o Now supports libsvm 2.4

  
Changes in Version 1.3-9:

  o rdiscrete() is now simply a wrapper for sample() and provided for backwards     compatibility only. 

  o Minor bug fixes in `svm' and `tune' (mostly interface issues). New
    plot function for objects of class `svm' working for the 2d-classification 
    case.

    
Changes in Version 1.3-7:

  o svm() now supports the `matrix.csr' format, as handled by the
   `SparseM' package. Predictors and response variable (if numeric) are scaled per
    default.
  o A new `plot' function for `svm' objects visualizes classification
    models by plotting data and support vectors in the data input
    space, along with the class borders.
  o A new generic `tune' function allows parameter tuning of arbitrary
    functions using, e.g., boot strapping, or cross validation.
    Several convenience wrappers (e.g., for svm, nnet, and rpart) do exist.

	
Changes in Version 1.3-3:

  o Bug fixes in various bclust routines: stop() if required packages
    are not found
  o svm() now interfaces LIBSVM 2.35 which is a bug fix release.
    A call with invalid parameters now no longer causes R to be
    terminated, and the C(++) code became completely silent.
  o Bugs fixed in fclustIndex function and print.fclust.  

    
Changes in Version 1.3-1:

  o Functions rmvnorm and dmvnorm for multivariate normal
    distributions have been moved to package mvtnorm.

  o Bug fixes in print.fclust and fclustIndex.

  o fixed floyd.c (ANSI C pedantic warnings)

  
Changes in Version 1.2-1:

  o Bug fixes in cmeans.c, cshell.c and scaclust.c (R header files
    included and unused variables removed)
  
  o Bug fixes in Rsvm.c and svm.R (incomplete list of returned Support 
    Vectors).

  o Encapsulate kmeans call in bclust() in a try construct, because
    kmeans gives an error when a cluster becomes empty (which can
    happen for almost every data set from time to time).

    
Changes in Version 1.2-0:

  o Added functions for bagged clustering, see help(bclust).

  o read.pnm() and write.pgm() have been removed from e1071, much
    improved versions can now be found in the new package pixmap. 

  o Lots of documentation updates and bugfixes.

  o Support Vector Machine interface now upgraded to libsvm V. 2.31
    featuring:
    - Multi-Class Classification
    - weighting of classes for C-classification (for asymmetric sample sizes)
    - nu-regression
    - Formula Interface
    - k-fold cross-validation
    In addition, an introductory article is provided in directory
    `docs/' (svmdoc.pdf).

  o classAgreement now features an option to match factor levels

  o updated API design for the fuzzy clustering functions
    (cmeans, cshell, scaclust). Documentation updates and function
    name changes (cmeanscl -> cmeans, validity.measures -> fclustIndex)