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Results

The "Results" tab allows the user toview the results of each clustering previously selected.

Results option sub-tab

The Results option sub-tab is used to restart the whole clustering, by pressing the Reset All Clustering button.

Or it is used to choose which results to export in csv. The user can choose to export the labels or the scores of each clustering. To do so, he just has to check on the left the results he wants to export and on the right, there are buttons to export either the labels Download Selected Clustering or the scores Download Selected Score.

Figure 8: Results option sub-tab.

Results sub-tab

Each clustering that has been previously selected is associated with a result sub-tab.

In each of the sub-tabs you will find a lot of information to visualize the results but also to check if the clustering was done in the right way.

He can then navigate between the various other sub-tabs to see the results of the classifications. In these sub-tabs, he can thus : * Choose the level of depth to be displayed (only available for the Multi-level classification) * Visualize the result of the classification by displaying the graph * To visualize the eigenvalues in a graph (if available) * To visualize the eigenspace of your choice (if available) * View the score table with all the scores that have been calculated (some scores will only be calculated if the real labels have been selected previously) * Display the labels table (available only if the real labels have been selected) * Display debugging information. Among this information, we find : * The logs of the classification algorithm * Eigenvalues in an array (if available) * The eigenvectors (if available) * The heatmap of the similarity matrix, to visualize if it has been calculated correctly (if available) * Additional scores useful to know if the clusters have been correctly built and if the result seems correct

Some of them are not available for all classifications, for example, if it is not a spectral classification, the information of the eigenvalues and eigenvectors will not be available.

The user has access to all the basic features of the R package. He can also visualize and interpret the results quickly, which allows him to know if they are good or not.

Figure 9: Example of results sub-tab.