06_multiclass accuracy_multi plot

[grayskripko]

In cell 35, there is a plot

Do I understand right that we have values of activations on the x-axis, not probabilities, as well as we pick sigmoid=False?
If so, why do limited with 0 and 1? Is it an unintentional error and they should have wide ranges?

[TannerGilbert]

Actually the x axis are the values generated by linespace (20 points from 0.05 to 0.95 as specified in the first row). The y axis represents the accuracy calculated with accuracy_multi. The reason sigmoid is set to false is that get_preds by default already applies the activation function as mentioned in the text above cell 34.

[grayskripko]

thank you @TannerGilbert for explanations.
To be honest, I did understand everything you said.
I understand the idea of linespace as well as the idea of sigmoid argument.

Could you please help me answer the questions below in the form they are formulated?
Thank you.

[TannerGilbert]

@grayskripko I'm not sure which questions you mean.

[grayskripko]

@TannerGilbert I meant "questions above" :)
Are there probabilities on the x-axis?

[TannerGilbert]

No, on the x-axis there are 29 points from 0.05 to 0.95 (created with linspace).

[grayskripko]

@TannerGilbert yep, they are points. I clearly understand it. On the other hand, they have meaning. So each point is an observation of 2 features. The second dimension of each point, the y-axis, is the accuracy. The first dimension is threshold of "X".
What is X?

[TannerGilbert]

The y-axis represents the accuracy and the x-axis represents the threshold used for the accuracy_multi method.

e.g. if you have three classes [car, dog, human], the threshold is 0.8 and your model outputs [0.9, 0.3, 0.85] you can say that you have a car and human in your image.

In the code in cell 35 we're trying out different threshold values to see which one gives the best accuracy for the task.

[grayskripko]

@TannerGilbert

your model outputs [0.9, 0.3, 0.85]

So it's a threshold of activations, not a threshold of probabilities, right?

[grayskripko]

I understood, finally. Out predicted activations were "sigmoided" before, so they are probabilities.