AlgorithmA set of rules to solve a problem in a number of steps.
Definitions:
A process or set of rules to be followed in calculations or other problem-solving operations, especially by a computer.
SupervisedA type of machine learning where an algorithm learns from example data and associated target responses.
Definitions:
Supervised learning is the machine learning task of learning a function that maps an input to an output based on example input-output pairs.
FeaturesAttributes used to describe data in machine learning.
Definitions:
In machine learning and pattern recognition, a feature is an individual measurable property or characteristic of a phenomenon being observed.
UnsupervisedA type of machine learning used to draw inferences from datasets consisting of input data without labeled responses.
Definitions:
Unsupervised learning is a type of self-organized Hebbian learning that helps find previously unknown patterns in data set without pre-existing labels.