Distance Transformation ======================= Transforms distances in a dataset. **Inputs** - Distances: distance matrix **Outputs** - 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. ![](images/DistanceTransformation-stamped.png) 1. Choose the type of [Normalization](https://en.wikipedia.org/wiki/Normalization_\(statistics\)): - **No normalization** - **To interval [0, 1]** - **To interval [-1, 1]** - [Sigmoid function](https://en.wikipedia.org/wiki/Sigmoid_function): 1/(1+exp(-X)) 2. Choose the type of Inversion: - **No inversion** - **-X** - **1 - X** - **max(X) - X** - **1/X** 3. Produce a report. 4. After changing the settings, you need to click *Apply* to commit changes to other widgets. Alternatively, tick *Apply automatically*. Example ------- 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](../unsupervised/distances.md) widget. In order to demonstrate how **Distance Transformation** affects the [Distance Matrix](../unsupervised/distancematrix.md), we created the workflow below and compared the transformed distance matrix with the "original" one. ![](images/DistanceTransformation-Example.png)