Table 6
Comparison of neural network performance for classifying dust species, and the fraction of predictions of the test data set that have 
to all the predictions from the test data set 
, in scenario 3 for case-2 as defined in Table 2.
| Classification accuracy rate (%) |  (%) |
|||
|---|---|---|---|---|
| S/N | Carbon dust | Mixed dust | Silicate dust | |
| 3 | 81 | 53 | 90 | 12 |
| 20 | 97 | 92 | 100 | 12 |
Notes. Two test cases with test data sets with S/N = 3 and S/N = 10, respectively, are evaluated. With the subset of JWST filters that are selected via the feature selection procedure as follows: (c): see the definitions in Table 2.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.