Figure 1.

A schematic depiction of supervised and unsupervised machine learning approaches

(A) An example of a supervised approach. Here, data points (circles) in ×1 and ×2 dimensions are labeled in magenta and green categories, allowing the model (dashed line) to be fitted.

(B) An example of an unsupervised approach. Here an algorithm attempts to detect patterns (clusters; dashed line) in unlabeled data (light blue circles).

For simplicity of graphical illustration, all the data points are depicted in a 2D space of ×1 and ×2. However, similar concepts apply to n-dimensional space. Dashed line represents an abstraction for a model or a decision boundary.