Chernoff Faces are a method for diagramming multiple variables of data at once through facial features (eyes, nose, hair, ears, mouth, eyebrows) with size, orientation, shape, color, and placement potentially representing different attributes of a single observation based on numeric values in a data set.
Our visual system is tuned to understand and remember human faces, so we are able to notice small differences and similarities within the data. However, for the same reason, this may lead to misinterpretation of data (especially without a key) as we have strong and varied personal associations with certain facial features.
An algorithm is used to translate the categories of raw data into a specific feature on the human face.
Examples:
The addition of a key is imperative and helpful to be able to interpret the data.
