Difference between revisions of "Orange: Distance Transformation"

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Transforms distances in a dataset.
 
Transforms distances in a dataset.
  
Inputs
+
==Input==
  
    Distances: distance matrix
+
Distances: distance matrix
  
Outputs
+
==Output==
  
    Distances: transformed distance matrix
+
Distances: transformed distance matrix
  
 
The Distances Transformation widget is used for the normalization and inversion of distance matrices. The normalization of data is necessary to bring all the variables into proportion with one another.
 
The Distances Transformation widget is used for the normalization and inversion of distance matrices. The normalization of data is necessary to bring all the variables into proportion with one another.
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[[File:DistanceTransformation-stamped.png|center|200px|thumb]]
 
[[File:DistanceTransformation-stamped.png|center|200px|thumb]]
  
    Choose the type of Normalization:
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* Choose the type of Normalization:
        No normalization
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** No normalization
        To interval [0, 1]
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** To interval [0, 1]
        To interval [-1, 1]
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** To interval [-1, 1]
        Sigmoid function: 1/(1+exp(-X))
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** Sigmoid function: 1/(1+exp(-X))
    Choose the type of Inversion:
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* Choose the type of Inversion:
        No inversion
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** No inversion
        -X
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** -X
        1 - X
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** 1 - X
        max(X) - X
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** max(X) - X
        1/X
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** 1/X
    Produce a report.
+
* Produce a report.
    After changing the settings, you need to click Apply to commit changes to other widgets. Alternatively, tick Apply automatically.
+
* After changing the settings, you need to click Apply to commit changes to other widgets. Alternatively, tick Apply automatically.
  
 
==Contoh==
 
==Contoh==

Revision as of 08:15, 29 January 2020

Sumber: https://docs.biolab.si//3/visual-programming/widgets/unsupervised/distancetransformation.html

Transforms distances in a dataset.

Input

Distances: distance matrix

Output

Distances: transformed distance matrix

The Distances Transformation widget is used for the normalization and inversion of distance matrices. The normalization of data is necessary to bring all the variables into proportion with one another.

DistanceTransformation-stamped.png
  • Choose the type of Normalization:
    • No normalization
    • To interval [0, 1]
    • To interval [-1, 1]
    • Sigmoid function: 1/(1+exp(-X))
  • Choose the type of Inversion:
    • No inversion
    • -X
    • 1 - X
    • max(X) - X
    • 1/X
  • Produce a report.
  • After changing the settings, you need to click Apply to commit changes to other widgets. Alternatively, tick Apply automatically.

Contoh

In the snapshot below, you can see how transformation affects the distance matrix. We loaded the Iris dataset and calculated the distances between rows with the help of the Distances widget. In order to demonstrate how Distance Transformation affects the Distance Matrix, we created the workflow below and compared the transformed distance matrix with the “original” one.

DistanceTransformation-Example.png


Referensi

Pranala Menarik