|
Confusion: To Dissimilarity...
|
|
A command that creates a Dissimilarity from every selected Confusion.
Settings
-
Normalize
-
when on, normalize rows by dividing each row element by the row sum. In this way you correct for unequal stimulus numbers.
-
No symmetrization, Average, Houtgast
-
determine the symmetrization procedure. See Confusion: To Similarity...
-
Maximum dissimilarity
-
determines the maximum dissimilarity possible. When the default value, 0.0, is chosen, maximumDissimilarity is calculated as the maximum element in the Similarity object.
Algorithm
We first transform the Confusion to a Similarity. See Confusion: To Similarity...
To obtain dissimilarities from similarities we "reverse" the latter:
|
dissimilarityij = maximumDissimilarity – similarityij |
© djmw 20040407