BNW using Octave instead of Matlab.

This version of BNW should perform the same as the original version. The only difference is that it uses Octave instead of Matlab when running BayesNet Toolbox during parameter learning.

I am calling this BNW_1.02. It can be accessed at:
compbio.uthsc.edu/BNW_1.02

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+Description of Datasets
+
+
+1. Title: Image Segmentation data
+
+2. Source Information
+   -- Creators: Vision Group, University of Massachusetts
+   -- Donor: Vision Group (Carla Brodley, brodley@cs.umass.edu)
+   -- Date: November, 1990
+ 
+3. Past Usage: None yet published
+
+4. Relevant Information:
+
+   The instances were drawn randomly from a database of 7 outdoor 
+   images.  The images were handsegmented to create a classification
+   for every pixel.  
+
+   Each instance is a 3x3 region.
+
+5. Number of Instances:  2310
+
+6. Number of Attributes: 19 continuous attributes
+
+7. Attribute Information:
+
+    1.  region-centroid-col:  the column of the center pixel of the region.
+    2.  region-centroid-row:  the row of the center pixel of the region.
+    3.  region-pixel-count:  the number of pixels in a region = 9.
+    4.  short-line-density-5:  the results of a line extractoin algorithm that 
+         counts how many lines of length 5 (any orientation) with
+         low contrast, less than or equal to 5, go through the region.
+    5.  short-line-density-2:  same as short-line-density-5 but counts lines
+         of high contrast, greater than 5.
+    6.  vedge-mean:  measure the contrast of horizontally
+         adjacent pixels in the region.  There are 6, the mean and 
+         standard deviation are given.  This attribute is used as
+        a vertical edge detector.
+    7.  vegde-sd:  (see 6)
+    8.  hedge-mean:  measures the contrast of vertically adjacent
+          pixels. Used for horizontal line detection. 
+    9.  hedge-sd: (see 8).
+    10. intensity-mean:  the average over the region of (R + G + B)/3
+    11. rawred-mean: the average over the region of the R value.
+    12. rawblue-mean: the average over the region of the B value.
+    13. rawgreen-mean: the average over the region of the G value.
+    14. exred-mean: measure the excess red:  (2R - (G + B))
+    15. exblue-mean: measure the excess blue:  (2B - (G + R))
+    16. exgreen-mean: measure the excess green:  (2G - (R + B))
+    17. value-mean:  3-d nonlinear transformation
+         of RGB. (Algorithm can be found in Foley and VanDam, Fundamentals
+         of Interactive Computer Graphics)
+    18. saturatoin-mean:  (see 17)
+    19. hue-mean:  (see 17)
+
+8. Missing Attribute Values: None
+
+9. Class Distribution: 
+
+   Classes: 1 = brickface, 
+	    2 = sky, 
+	    3 = foliage, 
+	    4 = cement, 
+	    5 = window, 
+	    6 = path, 
+	    7 = grass.
+
+