[mlpack-svn] r14466 - mlpack/trunk/doc/tutorials/det

[fastlab-svn at coffeetalk-1.cc.gatech.edu]

Author: rcurtin
Date: 2013-03-05 14:54:50 -0500 (Tue, 05 Mar 2013)
New Revision: 14466

Modified:
   mlpack/trunk/doc/tutorials/det/det.txt
Log:
The name of the executable changed.  Update documentation accordingly.


Modified: mlpack/trunk/doc/tutorials/det/det.txt
===================================================================
--- mlpack/trunk/doc/tutorials/det/det.txt	2013-03-05 16:58:50 UTC (rev 14465)
+++ mlpack/trunk/doc/tutorials/det/det.txt	2013-03-05 19:54:50 UTC (rev 14466)
@@ -47,11 +47,11 @@
    - \ref dtutils_util_funcs
  - \ref further_doc_det_tut
 
- at section cli_det_tut Command-Line 'dt_main'
+ at section cli_det_tut Command-Line 'det'
 The command line arguments of this program can be viewed using the '-h' option:
 
 @code
-$ ./dt_main -h
+$ ./det -h
 
 Density estimation with DET
 
@@ -139,15 +139,15 @@
 for more information).
 
 @code
-$ ./dt_main -S dataset.csv -v
+$ ./det -S dataset.csv -v
 @endcode
 
-By default, dt_main performs 10-fold cross-validation (using the
+By default, det performs 10-fold cross-validation (using the
 \f$\alpha\f$-pruning regularization for decision trees). To perform LOOCV
 (leave-one-out cross-validation), use the following command:
 
 @code
-$ ./dt_main -S dataset.csv -F 0 -v
+$ ./det -S dataset.csv -F 0 -v
 @endcode
 
 To perform k-fold crossvalidation, use \c -F \c k. There are certain other
@@ -157,14 +157,14 @@
 and the \c -N (\c --minimum_leaf_size) options.
 
 @code
-$ ./dt_main -S dataset.csv -M 20 -N 10
+$ ./det -S dataset.csv -M 20 -N 10
 @endcode
 
 In case you want to output the density estimates at the points in the training
 set, use the \c -s option to specify the output file.
 
 @code
-$ ./dt_main -S dataset.csv -s density_estimates.txt -v
+$ ./det -S dataset.csv -s density_estimates.txt -v
 @endcode
 
 @subsection cli_alt_reg_tut Alternate DET regularization
@@ -194,7 +194,7 @@
 estimates are to be output.
 
 @code
-$ ./dt_main -S dataset.csv -T test_points.csv -t test_density_estimates.txt -v
+$ ./det -S dataset.csv -T test_points.csv -t test_density_estimates.txt -v
 @endcode
 
 @subsection cli_ex3_de_p_tut Printing a trained DET
@@ -202,14 +202,14 @@
 A depth-first visualization of the DET can be obtained by using the \e -P flag.
 
 @code
-$ ./dt_main -S dataset.csv -P -v
+$ ./det -S dataset.csv -P -v
 @endcode
 
 To print this tree in a file, use the \e -p option to specify the output file
 along with the \e -P flag.
 
 @code
-$ ./dt_main -S dataset.csv -P -p tree.txt -v
+$ ./det -S dataset.csv -P -p tree.txt -v
 @endcode
 
 @subsection cli_ex4_de_vi_tut Computing the variable importance
@@ -220,13 +220,13 @@
 features.
 
 @code
-$ ./dt_main -S dataset.csv -I -v
+$ ./det -S dataset.csv -I -v
 @endcode
 
 To print this in a file, use the \e -i option
 
 @code
-$ ./dt_main -S dataset.csv -I -i variable_importance.txt -v
+$ ./det -S dataset.csv -I -i variable_importance.txt -v
 @endcode
 
 @subsection cli_ex5_de_lm Leaf Membership
@@ -239,11 +239,11 @@
 present in this set using the \e -C option.
 
 @code
-$ ./dt_main -S dataset.csv -L labels.csv -C <number-of-classes> -v
+$ ./det -S dataset.csv -L labels.csv -C <number-of-classes> -v
 @endcode
 The leaf membership matrix is output into a file called 'leaf_class_membership.txt' by default. An user-specified file can be used by utilizing the \e -l option.
 @code
-$ ./dt_main -S dataset.csv -L labels.csv -C <number-of-classes> -l leaf_class_membership_file.txt -v
+$ ./det -S dataset.csv -L labels.csv -C <number-of-classes> -l leaf_class_membership_file.txt -v
 @endcode