*********** Forests.nns is a NeuNet Pro Sample File ***********

This file contains special properties that allow NeuNet Pro to recognize it
as authorized NeuNet sample data.  Anyone using the unlicensed version
of NeuNet Pro is welcome to experiment with this sample data.
Please do not modify this file, or it will lose its status as authorized sample data.

For further information about Neunet Pro and additional sample data,
please visit the NeuNet Pro website at http://www.cormactech.com/neunet

All of this data has been collected from publicly available sources.
CorMac Technologies Inc. does not guarantee the accuracy of the data.
This data is intended solely for experimental purposes.

This data contains 581,012 records and 56 fields.
The included NeuNet Pro SFAM project was trained on a random sample of 32,000 and produces an accuracy of 68% on the remainder.
The original data has been randomly shuffled.

    ***************  More about the Forests Data *******************

The Forest CoverType dataset

1.	Title of Database:

	Forest Covertype data

2.	Sources:

	(a) Original owners of database:
		Remote Sensing and GIS Program
		Department of Forest Sciences
		College of Natural Resources
		Colorado State University
		Fort Collins, CO  80523
		(contact Jock A. Blackard, jblackard/wo_ftcol@fs.fed.us
		      or Dr. Denis J. Dean, denis@cnr.colostate.edu)

	NOTE:	Reuse of this database is unlimited with retention of 
		copyright notice for Jock A. Blackard and Colorado State University.

	(b) Donors of database:
		Jock A. Blackard (jblackard/wo_ftcol@fs.fed.us)
		USDA Forest Service
		3825 E. Mulberry
		Fort Collins, CO  80524  USA

		Dr. Denis J. Dean (denis@cnr.colostate.edu)
		Associate Professor
		Department of Forest Sciences
		Colorado State University
		Fort Collins, CO  80523  USA

		Dr. Charles W. Anderson (anderson@cs.colostate.edu)
		Associate Professor
		Department of Computer Science
		Colorado State University
		Fort Collins, CO  80523  USA

	(c) Date donated:  August 1998

3.	Past Usage:

	Blackard, Jock A.  1998.  "Comparison of Neural Networks and
		Discriminant Analysis in Predicting Forest Cover Types."
		Ph.D. dissertation.  Department of Forest Sciences.
		Colorado State University.  Fort Collins, Colorado.

	-- Classification performance
		-- first 11,340 records used for training data subset
		-- next 3,780 records used for validation data subset
		-- last 565,892 records used for testing data subset
		-- 70% backpropagation
		-- 58% Linear Discriminant Analysis

4.	Relevant Information Paragraph:

	Predicting forest cover type from cartographic variables only
	(no remotely sensed data).  The actual forest cover type for
	a given observation (30 x 30 meter cell) was determined from
	US Forest Service (USFS) Region 2 Resource Information System 
	(RIS) data.  Independent variables were derived from data
	originally obtained from US Geological Survey (USGS) and
	USFS data.  Data is in raw form (not scaled) and contains
	binary (0 or 1) columns of data for qualitative independent
	variables (wilderness areas and soil types).

5.	Number of instances (observations):  581,012

6.	Number of Attributes:	12 measures, but 54 columns of data
				(10 quantitative variables, 4 binary
				wilderness areas and 40 binary
				soil type variables)

7.	Attribute information:

Given is the attribute name, attribute type, the measurement unit and
a brief description.  The forest cover type is the classification problem.
The order of this listing corresponds to the order of numerals along the
rows of the database.

Name					Data Type	Measurement			Description

Elevation				quantitative	meters				Elevation in meters
Aspect					quantitative	azimuth				Aspect in degrees azimuth
Slope					quantitative	degrees				Slope in degrees
Horizontal_Distance_To_Hydrology	quantitative	meters				Horz Dist to nearest surface water features
Vertical_Distance_To_Hydrology		quantitative	meters				Vert Dist to nearest surface water features
Horizontal_Distance_To_Roadways		quantitative	meters				Horz Dist to nearest roadway
Hillshade_9am 				quantitative	0 to 255 index			Hillshade index at 9am, summer solstice
Hillshade_Noon				quantitative	0 to 255 index			Hillshade index at noon, summer soltice
Hillshade_3pm				quantitative	0 to 255 index			Hillshade index at 3pm, summer solstice
Horizontal_Distance_To_Fire_Points	quantitative	meters				Horz Dist to nearest wildfire ignition points
Wilderness_Area (4 binary columns)	qualitative	0 (absence) or 1 (presence)	Wilderness area designation
Soil_Type (40 binary columns)		qualitative	0 (absence) or 1 (presence)	Soil Type designation
Cover_Type (7 types)			integer		1 to 7				Forest Cover Type designation

Code Designations:

Wilderness Areas:  	1 -- Rawah Wilderness Area
			2 -- Neota Wilderness Area
			3 -- Comanche Peak Wilderness Area
			4 -- Cache la Poudre Wilderness Area

Soil Types:		1 to 40 : based on the USFS Ecological
			Landtype Units for this study area.

Forest Cover Types:	1 -- Spruce/Fir
			2 -- Lodgepole Pine
			3 -- Ponderosa Pine
			4 -- Cottonwood/Willow
			5 -- Aspen
			6 -- Douglas-fir
			7 -- Krummholz

NOTE:  Summary statistics not included in this documentation.

8.	Missing Attribute Values:  None.

9.	Class distribution:

		Number of records of Spruce-Fir: 	211840 
		Number of records of Lodgepole Pine: 	283301 
		Number of records of Ponderosa Pine: 	 35754 
		Number of records of Cottonwood/Willow:   2747 
		Number of records of Aspen: 		  9493 
		Number of records of Douglas-fir: 	 17367 
		Number of records of Krummholz: 	 20510 	
		Number of records of other: 		     0 	
		Total records:				581012

Jock A. Blackard