Neighbors ========= Compute nearest neighbors in data according to reference. **Inputs** - Data: An input data set. - Reference: A reference data for neighbor computation. **Outputs** - Neighbors: A data table of nearest neighbors according to reference. 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. ![](images/neighbours-stamped.png) 1. Information on the input data. 2. Distance measure for computing neighbors. Supported measures are: Euclidean, Manhattan, Mahalanobis, Cosine, Jaccard, Spearman, absolute Spearman, Pearson, absolute Pearson. 3. Number of neighbors on the output. 4. If *Exclude rows (equal to) references* is ticked, data instances that are highly similar to the reference (distance < 1e-5), will be excluded. 5. Click *Apply* to commit the changes. To communicate changes automatically tick *Apply Automatically*. 6. Access widget help. Examples -------- In the first example, we used *iris* data and passed it to **Neighbors** and to [Data Table](../data/datatable.md). In **Data Table**, we selected an instance of iris, that will serve as our reference, meaning we wish to retrieve 10 closest examples to the select data instance. We connect **Data Table** to **Neighbors** as well. We can observe the results of neighbor computation in **Data Table (1)**, where we can see 10 closest images to our selected iris flower. ![](images/neighbours-example1.png) 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. ![](images/neighbours-example-multiple.png) 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. 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)**. ![](images/neighbours-example2.png)