Changes in version 6.2:

1. Changed algorithm for splits on categorical variables in classification

2. Added new data formats: C4.5 and ARFF

Changes in version 6.1:

1. Fixed a bug that wrote messages to fort file during batch file creation

2. Fixed a bug in calculation of estimated class priors when there is
   a weight variable

Changes in version 6.0.1:

1. Fixed a bug that miscalculated test sample misclassification cost
   when some classes are absent in the test sample

Changes in version 6.0:

1. Added classification tree capability

2. Added random forest capability

3. Made some changes to split selection algorithms

Changes in version 5.3:

1. Corrected a bug that affected latex files when there are no
   categorical variables

Changes in version 5.2:

1. Changed variable selection for interaction tests to use two-levels
   of splits

2. Reverted to true stepwise and ancova fitting for split selection
   for these options

Changes in version 5.1:

1. Fixed a bug caused by missing values while reading data

Changes in version 5.0:

1. Improved approach to interaction tests to account for their number

2. Changed default SE for constant fit to 0

3. Added option for variable importance scores and for identification
   of unimportant variables

Changes in version 4.4:

1. Fixed a bug in split variable selection routine that affected "s"
   variables

Changes in version 4.3:

1. Made the program output progress after each CV iteration.

2. Extended the length of variable names from 8 to 10 for data
   conversion to SAS.

3. Added code for PROC GLM and PROC REG if SAS output is selected.

4. Added a suggestion to use white or yellow colors if leaf node
   numbers are selected.

5. Allow execution to continue if an excluded variable contains values
   longer than 20 characters.

6. Allow option 3 (data conversion) to proceed if there are data
   values longer than 20 characters, with a warning that they are
   truncated.

Changes in version 4.2:

1. Corrected a bug that affects relative risk regression when some D
   or T variables have missing values.

2. Added an option for weighted or unweighted error estimation when a
   weight variable exists. The default is unweighted.

3. Changed from zero-truncated normal to 1-df chi-square statistic for
   split variable selection.

Changes in version 4.1:

1. Corrected a bug in output for truncation type 2.

2. Reverted default value of mindat to 0 for stepwise option.

Changes in version 4.0:

1. Added an option for least median of squares (robust) regression for
   multiple and best simple linear fitting.

2. Increased amount of information output to (optional) file containing
   names and regression coefficients in leaf nodes.

3. Changed absolute z to truncated z for variable selection and
   bootstrap bias correction.

4. Added an option to save multiple regression coefs in a separate file.

5. Added an option to fit piecewise least-squares multiple linear
   regression without intercept terms.

6. Added an option to not truncate, truncate fitted values, or
   truncate x-values before prediction.

7. Added option to drop insignificant leading powers in polynomial models.

8. Added option for stepwise simple linear ANCOVA.

9. Allowed stepwise linear option to use "c" or "b" categorical variables.

10. Fixed a bug that affected datasets with missing values but without
    weight variables.

11. Fixed a bug in split point selection to use total mean deviance
    instead of total deviance.

12. Added option for all subsets regression.

13. Improved search over split points for non-exhaustive search.

14. Changed option for non-exhaustive search from fraction to number.

Changes in version 3.1:

1. For stepwise and polynomial regression, added option to write the
   leaf node number and the selected regressors into a separate file.

2. Added option for colored leaf nodes and improved font sizes in
   LaTeX tree diagrams.

3. Added optional file of node IDs and fitted values of a column to
   indicate training observation.

4. Added R-squared value for tree model (least-squares fit only).

5. Fixed bug in interaction test. Now preference for "c" variable is
   given on to multiple linear regression.

6. Increased number of trees in pruning sequence.