CODEWITHSUNDEEP
machine-learningneural-networkazure-machine-learning-servicemulticlass-classification
Alexander Johansson
Alexander Johansson

Reputation: 103

How to understand output from a Multiclass Neural Network

Built a flow in Azure ML using a Neural network Multiclass module (for settings see picture). enter image description here

Some more info about the Multiclass:

enter image description here

The data flow is simple, split of 80/20.

enter image description here

Preparation of the data is made before it goes into Azure. Data looks like this: enter image description here

My problem comes when I want to make sense of the output and if possible transform/calculate the output to probabilities. Output looks like this: enter image description here

My question: If scored probabilities output for my model is 0.6 and scored labels = 1, how sure is the model of the scored labels 1? And how sure can I be that actual outcome will be a 1?

Can I safely assume that a scored probabilities of 0.80 = 80% chance of outcome? Or what type of outcomes should I watch out for?

Upvotes: 0

Views: 278

Answers (1)

desertnaut
desertnaut

Reputation: 60338

To start with, your are in a binary classification setting, not in a multi-class one (we normally use this term when number of classes > 2).

If scored probabilities output for my model is 0.6 and scored labels = 1, how sure is the model of the scored labels 1?

In practice, the scored probabilities are routinely interpreted as the confidence of the model; so, in this example, we would say that your model has 60% confidence that the particular sample belongs to class 1 (and, complementary, 40% confidence that it belongs to class 0).

And how sure can I be that actual outcome will be a 1?

If you don't have any alternate means of computing such outcomes yourself (e.g. a different model), I cannot see how this question is different from your previous one.

Can I safely assume that a scored probabilities of 0.80 = 80% chance of outcome?

This is the kind of statement that would drive a professional statistician mad; nevertheless, the clarifications above regarding the confidence should be enough for your purposes (they are enough indeed for ML practitioners).

My answer in Predict classes or class probabilities? should also be helpful.

Upvotes: 3

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