Methods, computer systems, computer-storage media, and graphical user interfaces are provided for visualizing a performance of a machine-learned model. An interactive graphical user interface includes an item representation display area that displays a plurality of item representations corresponding to a plurality of items processed by the machine-learned model. The plurality of item representations are arranged according to scores assigned to the plurality of items by the machine-learned model. Further, each of the plurality of item representations is visually configured to represent a label assigned to a corresponding item.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. One or more computer-readable media having computer-executable instructions embodied thereon that, when executed by a computing device, cause the computing device to generate a graphical user interface (GUI) for visualizing a performance of a machine-learned model, the GUI comprising: an item representation display area that displays a plurality of item representations corresponding to a plurality of items processed by the machine-learned model, each of the plurality of item representations arranged according to a score assigned to an item corresponding to the each of the plurality of item representations by the machine-learned model, and the each of the plurality of item representations being visually configured to represent a label assigned to an item corresponding to the each of the plurality of item representations. 2. The GUI of claim 1, wherein the each of the plurality of item representations being visually configured to represent an assigned label comprises the each of the plurality of item representations having a color indicating the assigned label. 3. The GUI of claim 1, wherein the each of the plurality of item representations is located at a position oriented along a horizontal axis, the position corresponding to the score assigned to the item corresponding to the each of the plurality of item representations. 4. The GUI of claim 1 further comprising a prediction threshold indicator usable for selecting a prediction threshold. 5. The GUI of claim 4, wherein the prediction threshold indicator visually separates a first subset of the plurality of item representations from a second subset of the plurality of item representations, the first subset of the plurality of item representations corresponding to a first subset of the plurality of items that the machine-learned model has associated with a first class, and the second subset of the plurality of item representations corresponding to a second subset of the plurality of items that the machine-learned model has associated with a second class. 6. The GUI of claim 1, further comprising an item display area that displays information associated with at least one of the plurality of items. 7. The GUI of claim 1, wherein a subset of the plurality of item representations is further visually configured to indicate a relationship among a subset of the plurality of items corresponding to the subset of the plurality of item representations. 8. The GUI of claim 7, wherein the relationship comprises a common attribute shared by the subset of the plurality of items, and wherein the subset of the plurality of item representations is highlighted to indicate that each item of the corresponding subset of the plurality of items has a common attribute. 9. The GUI of claim 7, wherein the subset of the plurality of item representations is highlighted to indicate that each item of the corresponding subset of the plurality of items is most similar to a selected item. 10. One or more computer-readable media having computer-executable instructions embodied thereon that, when executed by a computing device, cause the computing device to perform a method for displaying performance data of a machine-learned model, the method comprising: receiving a plurality of training items that have been processed by the machine-learned model; receiving a plurality of test items that have been processed by the machine-learned model; generating a training item representation for each of the plurality of training items and generating a test item representation for each of the plurality of test items; and displaying each of the training item representations corresponding to the each of the plurality of training items and displaying each of the test item representations corresponding to the each of the plurality of test items on a graphical user interface (GUI), the GUI comprising: a training item display area that displays the each of the training item representations corresponding to the each of the plurality of training items, wherein a location of a particular training item representation is based on a score assigned to the particular training item representation's corresponding training item by the machine-learned model, and a test item display area that displays the each of the test item representations corresponding to the each of the plurality of test items, wherein a location of a particular test item representation is based on a score assigned to the particular test item representation's corresponding test item by the machine-learned model. 11. The media of claim 10, wherein a visual configuration of a particular training item representation is based on a label assigned to the particular training item representation's corresponding training item, and a visual configuration of a particular test item representation is based on a label assigned to the particular test item representation's corresponding test item. 12. The media of claim 11, further comprising: receiving updated information that has been processed by the machine-learned model; receiving updated scores for the plurality of training items and the plurality of test items, the updated scores based on the updated information; and based on the updated scores, updating the display of the each of the training item representations and the each of the test item representations on the GUI. 13. The media of claim 12, wherein the updated information comprises additional training items or test items. 14. The media of claim 12, wherein the updated information comprises an input of a feature. 15. The media of claim 12, wherein the updating the display comprises modifying at least one test item representation or training item representation, the at least one test item representation or training item representation corresponding to a test item or a training item, respectively, having an updated score that is different from the score assigned prior to receiving the updated information. 16. The media of claim 12, further comprising: receiving a selection of at least one of a test item representation or a training item representation; and in response to the received selection, on the GUI, displaying information associated with the selected at least one of the test item representation or the training item representation. 17. The media of claim 16, wherein the displayed information comprises a selected item corresponding to the selected at least one of the test item representation or the training item representation, the selected item's label, and the selected item's assigned score. 18. One or more computer-readable media having computer-executable instructions embodied thereon that, when executed by a computing device, cause the computing device to generate a graphical user interface (GUI) for visualizing a performance of a machine-learned model, the GUI comprising: a training item display area that displays a plurality of training item representations, each of the plurality of training item representations representing a training item and a predetermined training item label associated with the training item, and the each of the plurality of training item representations having a location that corresponds to a training item score assigned to the respective training item by the machine-learned model; a test item display area that displays a plurality of test item representations, each of the plurality of test item representations representing a test item and a predetermined test item label associated with the test item, and the each of the plurality of training item representations having a location that corresponds to a test item score assigned to the respective test item by the machine-learned model; and a configurable prediction threshold indicator usable for selecting a prediction threshold and visualizing an impact of the selected prediction threshold on the performance of the machine-learned model. 19. The GUI of claim 18, further comprising a performance display area that displays a precision value and a recall value associated with a selected prediction threshold. 20. The GUI of claim 18, wherein the machine-learned model is at least one of a binary classification model, a multi-class classification model, an entity extraction model, or a ranking model, and wherein the GUI further comprises a plurality of class display areas.