Run Neural Network Module

Much of the documentation found in this section is also available from readme.txt, the guide to DataXplore.exe

To run DataXplore

Select 'Run Neural Network Module...' from the SDM menu.

This will launch DataXplore, which is a separate MS Windows program from ArcView.

While DataXplore is running, ArcView is fully accessible.

The remainder of this section describes how to use DataXplore with reference to Arc-SDM and the input files generated in the previous step.

• Radial Basis Functional Link Network
• Fuzzy Clustering

To perform Radial Basis Functional Link Network analysis (RBFLN)

there are three steps:

• training
• testing
• classification

Training

Click the 'Train' button to display the following dialog:

Select the file that contains your training data and click OK. The default name for neural network training data files generated from Arc-SDM is train#.dta.

The RBFLN parameter dialog is then displayed:

The parameters in the box 'RBFLN Parameters From data File' are read from the training data file specified in the previous step.

Click 'Start Train'. A report in the following format is displayed:

Contents of the report

No. of Hidden Layers -
No. of Input Vectors - the number of training vectors (unique conditions at the location of training points) in the training data file
No. of Unique Targets - this will always be 2, either 0 or 1, representing the presence or absence of a mineral occurrence
Total iterations - DataXplore parameter set in the parameter dialog. 200 is the default.
SSE - Sum Squared Error

Result of Training

Column 1: Vector No. - an integer uniquely identifying each vector
Column 2: Target - contains values of either 0 or 1. 0 indicates the absence of a mineral occurrence, 1 indicates presence.
Column 3: Actual Output - The actual value that was calculated for each training vector. The range of values is 0 to 1.
Column 4 - n: The input data. These are the actual values read from the training data file. If the file was generated by Arc-SDM, these values were derived from a unique conditions attribute table. The values for each evidential theme have been normalized or scaled between 0 and 1, and an area weighted average of known values has been calculated and used to define areas where data has been identified as missing.

To save this report to a file

You can optionally save the contents of this report to a text file for later inspection or reporting purposes. To do this,

1. Click 'Print ListBox Content to Temporary File'.
2. Specify a filename and location when prompted.

Save the results of the training session

1. Click 'Save Result as .par and Return'.
2. Specify a filename and location when prompted.

This file must created for input into the testing and classifying steps that follow.

You will be returned to the RBFLN parameter dialog.

Click 'Return to Main Menu'.

Testing

Click the 'Test' button.

Select the file that contains the data to be classified and click OK. The default name for neural network training data files generated from Arc-SDM is class#.dta.

You will then be prompted to select an RBFLN Test Parameter (*.par) file

1. Select the that you just generated in the training step.
2. Click 'Open'.

The test is performed and the following report is displayed:

Report Contents

Input Vectors Dimension - the number of components in an input vector. If the data file was generated by Arc-SDM, this is the number of evidential themes.
No. of Hidden Layers - number of training vectors
Target Vectors Dimension - this is always 1
No. of Input Vectors - this is the number of unique conditions written to the data file
SSE - Sum Squared Error

There are two targets, 0 and 1. In the example of the screen-captured reported above, 2096 vectors (or unique conditions) were classified as 0 and 1366 were classified as 1. The assignment of vectors to either class 0 or 1 is done by rounding the value calculated by the RBFLN. Arc-SDM will read the calculated values rather than the classified (rounded) value.

Result of RBFLN Test

Column 1: Vector No. - an integer uniquely identifying each vector (or unique condition)
Column 2: Class No. - the class to which the vector has been classified

To save this report to a file

You can optionally save the contents of this report to a text file for later inspection or reporting purposes. To do this,

1. Click 'Print ListBox Content to temporary file'.
2. Specify a filename and location when prompted.
3. Click 'Save'.
4. Click 'Return' to return to the main DataXplore dialog.

Classify

The steps for classifying data are the same as those taken for testing the classification in the preceding section, with the exception that results are saved to a permanent file that can be subsequently read by Arc-SDM.

Click the 'Classify' button.

When prompted, select the file containing the data to classify. If generated by Arc-SDM, the default name is class#.dta and click 'Open'.

When prompted, select the file containing the parameter file that was the result of the training step. Its extension is .par. Click 'Open'.'

When processing is complete, a report will be displayed with the following format:

The information reported in the report header is the same as shown an described in the preceding section about the testing process. The values reported should be identical.

Additional information is reported in the results section, as follows:

Result of RBFLN Classify

To save this report to a file

You can optionally save the contents of this report to a text file for later inspection or reporting purposes. To do this,

1. Click 'Print ListBox Content to temporary file'.
2. Specify a filename and location when prompted.
3. Click 'Save'.

Save the results of the RBFLN classification session

1. Click 'Save Results as .rbn and Return'.
2. Specify a filename and location when prompted.

This file must be saved if you want to read the results back into ArcView via Arc-SDM.

You will be returned to the main DataXplore dialog.

Fuzzy Clustering: Fuzzy (Unsupervised)

There are two steps in doing a classification by fuzzy clustering:

• Training
• Classification

Training

Click the 'Train' button located in the box labelled 'Fuzzy (Unsupervised)' on the main DataXplore dialog.

This will a dialog prompting you to select a 'Fuzzy Train Data File'. The fuzzy clustering algorithm trains using the complete data set that is to be classified. If your input files were generated by Arc-SDM, this file is the one that contains the entire unique conditions table information. The default name was class#.dta.

Select the file to use.

Click 'Open'.

The following dialog will be displayed:

Accept the default parameters as displayed.

Click 'Start Clustering'.

When the clustering processes are complete, a report is displayed in the following format:

Fuzzy Clustering Result

Number of Classes - This is the number of classifications that DataXplore defined from the data.

Center[i] - the values that define the center of each cluster. The number of dimensions equals the number of input evidential themes.

For each Class, the following information is reported:

Vectors Number - the number of vectors (unique conditions) belonging to the class
Weighted Fuzzy Variance (WFV) - the value for the weighted variance of the class
Vector Index in this Class - a list o1f integers identifying the vectors (unique conditions) that belong to the class
Clustering Validity (1/XieBeni) - a measure of the validity of the clustering results. A value !!!!

Merge

You can merge classes by clicking the 'Merge' button.

You may want to do this if:

• you want to deal with fewer classes in your results
• the value of the clustering validity measure is too low

When the merge process is complete, the message 'Merge finished' will be displayed at the top of an updated report. There may be a point at which the algorithm cannot merge the data into fewer classes than currently exist.

To save this report to a file

You can optionally save the contents of this report to a text file for later inspection or reporting purposes. To do this,

1. Click 'Save ListBox Content to temporary file'.
2. Specify a filename and location when prompted.
3. Click 'Save'.

When you are satisfied with the number of classes, click 'Finish'. This will prompt you to save the results of the clustering to a Fuzzy Cluster Result Center file (*.cen).

You must save the results of the clustering step for input into the Classify step that follows.

After you have saved the .cen file, click 'Return'.

Classify

Click the 'Classify' button.

Select the 'Fuzzy Classify Data file'. This is the same file that was selected as the 'Fuzzy Train Data File' in the preceding step. If generated by Arc-SDM, it contains the complete unique conditions table information and a name of class#.dta was proposed by default.

Click 'Open'.

When prompted, select the Fuzzy Classify Center file generated in the training step:

The results of the classification are reported in a similar report to the one created during the training step. It can be saved by clicking 'Save ListBox Content to temporary file' and specifying a name and location for the file.

Click 'Finish'.

You will be prompted to save a Fuzzy Classify Result file (.fuz). Specify the file name and click 'Save'. This file is required to read the results of fuzzy clustering back into ArcView via Arc-SDM.