Human-in-the-loop Machine Learning

Marco Brambilla
Dec 12, 2017 · 2 min read

A crucial requirement for supervised machine learning is to have access to good data. But another need is to provide your training phase with appropriate input from domain experts.

The crucial question then is:

if you have access to a highly valuable domain expert, how can you maximise the value you can extract from his time?

As a typical example of supervised approach, we pick classification. Here are some specific use cases where the domain experts are put at good use.

Labeling

Redefining Class Labels

This is called constraint-based classification, and it’s actually a semi-supervised method for rethinking class definitions.

(Very) Noisy Labels

This story is inspired by a keynote speech by Carla E. Brodley, from Northeastern University, given at the IEEE BigData Conference 2017.

Off-the-grid: digital vs. physical

Reflections on data-driven innovation for our society

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