This graph shows the F1 scores of the selected filter over time. The F1-score, is a measure of a model's accuracy on a dataset. It is used to evaluate binary classification systems, which classify examples into 'positive' or 'negative'. F1-score ranges between 0 and 1. The closer it is to 1, the better the model.
The number of feedback items that have been recieved on the given filter over a period of time.
Different types of metrics used to evaluate your ML system over time.
98.8%
blue_mattress_queen.png
97.8%
RedWagon.png
82.3%
doggy_car_seat.jpg
99.1%
blue_mattress_king.png
96.4%
HalloweenDecor.jpg
98.4%
taco-cart.png
99.2%
pig_cat_pajamas.png