Introduction to Inductive Learning in Artificial Intelligence
Understanding the process of inferring classification concepts from raw data
Machine learning is one of the most important subfields of artificial intelligence. It has been viewed as a viable way of avoiding the knowledge bottleneck problem in developing knowledge-based systems.
Inductive Learning, also known as Concept Learning, is how A.I. systems attempt to use a generalized rule to carry out observations.
Inductive Learning Algorithms (APIs) are used to generate a set of classification rules. These generated rules are in the "If this, then that" format.
These rules determine the state of an entity at each iteration step in Learning and how the Learning can be effectively changed by adding more rules to the existing ruleset.
When the output and examples of the function are fed into the A.I. system, inductive Learning attempts to learn the function for new data.
The Fundamental Concept of Inductive Learning
There are two methods for obtaining knowledge in the real world: first, from domain experts, and second, from machine learning.
