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An introduction to AutoML
Once the model is trained you can access the results from the console (Figure 68). In
this case we achieved a precision of 81.18% and a recall of 76.65%. You can play with
the model, for instance increasing the number of labeled videos available, to see how
the performance will change:
Figure 70: AutoML Video Intelligence – evaluating the results
Let's have a detailed look at the results via the EVALUATE tab. For instance,
we can analyze the precision/recall graph for different levels of threshold (see
Figure 71) and the confusion matrix showing examples of wrong classification of
shots (see Figure 72):
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