Train a classifier to differentiate between dark and light colors.
A machine learning classifier is a function that classifies objects. It is created by training on a set of examples rather than by explicit programming. Training data can be numerical, textual, sounds and images, as well as combinations of these.
Collect training examples
Get a color from its hexadecimal RGB color value:
Get some dark colors:
Get some light colors:
Construct a training set where each training value is assigned the correct class:
Train a classifier
Use the training set to train a classifier:
Test the classifier
Give the classifier a new color. It will infer, based on the training data, how to classify the color:
Get the classifier’s degree of confidence in what it has inferred, expressed as the probabilities of membership in each class:
Classify a list of colors:
Get information about the classifier
Get a report of the properties of the classifier: