Generate Random Training Points
The RBFLN neural network object requires two sets of training points:
The two sets of points (locations) are combined as training data.
This second type of data set is often not readily available so this function offers one way of approximating such a data set. The idea is to generate a set of points in parts of the study area where there is a very low probability of the object occurring.
One possibility for applying the function is to generate a probability map (response theme) using the weights of evidence or logistic regression methods and then generate a set of random points in areas of very low probability. This can be done as follows:
In this example, the
threshold should be lower than the prior probability. The
prior probability can be found in the third column of the
last row of the weights table associated with the
response theme, or can be reported by clicking the button
in the deposit training point theme properties dialog.
This dialog is displayed by clicking the 'Properties'
button in the 'Analysis Parameters' dialog.
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General Application
The 'Generate Random Training Points' function can use any grid theme in the active view. If a floating point grid theme is selected, the threshold value must be entered by the user. The minimum and maximum values in the grid theme are reported as guidance and the default value is the midpoint between these two.
For example, in this portion of the 'Non-deposit Training Points' dialog, for the selected theme (not shown) the minimum value is 0, the maximum is 1 and the default value is 0.5. |
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