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Copy file name to clipboardExpand all lines: doc/visual-programming/source/widgets/data/neighbors.md
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@@ -6,21 +6,22 @@ Compute nearest neighbors in data according to reference.
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**Inputs**
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- Data: An input data set.
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- Reference: A reference data instance for neighbor computation.
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- Reference: A reference data for neighbor computation.
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**Outputs**
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- Neighbors: A data table of nearest neighbors according to reference.
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The **Neighbors** widget computes nearest neighbors for a given reference and for a given distance measure.
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The **Neighbors** widget computes nearest neighbors for a given reference and for a given distance measure. The reference can be either one instance or more instances. In the case with one reference widget outputs closest `n` instances from data where `n` is set by the **Number of neighbors** option in the widget. When reference contains more instances widget computes the combined distance for each data instance as a minimum of distances to each reference. Widget outputs `n` data instances with lowest combined distance.
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1. Information on the input data.
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2. Distance measure for computing neighbors. Supported measures are: Euclidean, Manhattan, Mahalanobis, Cosine, Jaccard, Spearman, absolute Spearman, Pearson, absolute Pearson. If *Exclude references* is ticked, data instances that are highly similar to the reference (distance < 1e-5), will be excluded.
4. Click *Apply* to commit the changes. To communicate changes automatically tick *Apply Automatically*.
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5. Access widget help.
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4. If *Exclude rows (equal to) references* is ticked, data instances that are highly similar to the reference (distance < 1e-5), will be excluded.
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5. Click *Apply* to commit the changes. To communicate changes automatically tick *Apply Automatically*.
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6. Access widget help.
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Examples
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We can observe the results of neighbor computation in **Data Table (1)**, where we can see 10 closest images to our selected iris flower.
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Now change the selection **Data Table** to multiple examples. As a result, we get instances with closest combined distances to the references. The method computes the combined distance as a minimum of distances to each reference.
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Another example requires the installation of Image Analytics add-on. We loaded 15 paintings from famous painters with **Import Images** widget and passed them to **Image Embedding**, where we selected *Painters* embedder.
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Then the procedure is the same as above. We passed embedded images to **Image Viewer** and selected a painting from Monet to serve as our reference image. We passed the image to **Neighbors**, where we set the distance measure to *cosine*, ticked off *Exclude reference* and set the neighbors to 2. This allows us to find the actual closest neighbor to a reference painting and observe them side by side in **Image Viewer (1)**.
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