playground, A4, ethics tie-in A4.4.1

Machine learning, two features at a time

A k-nearest-neighbours classifier and its decision boundary, live. The ethics behind it

Dataset

Each dot is a student: hours studied across, hours slept up. Green passed the exam. Clean clusters: an easy job for any classifier.

The fairness readout this page is named for appears when you switch the dataset picker (top right) to the biased loans example.

Filled dots = training data (what the model learns from), outlined = test data (what it is judged on)

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playground, A4, ethics tie-in A4.4.1

A k-nearest-neighbours classifier and its decision boundary, live. The ethics behind it

Dataset

Each dot is a student: hours studied across, hours slept up. Green passed the exam. Clean clusters: an easy job for any classifier.

The fairness readout this page is named for appears when you switch the dataset picker (top right) to the biased loans example.

Filled dots = training data (what the model learns from), outlined = test data (what it is judged on)