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Confusion: To Dissimilarity...
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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