Question

Machine learning vs rule based system

Answer 1

Answer:---------
Machine learning vs rule based system:-------------

Rules-Based Systems:-----------
Rules-based systems are a simple kind of artificial intelligence, which use a series of IF-THEN statements that guide a computer to reach a conclusion or recommendation.

Two Key Components:-------
A rules-based system is built on two main components: a set of facts about a situation, and a set of rules for how to deal with those facts:

1. A set of facts. Also known as the knowledge base. These facts are a combination of data, such as income and a condition such as ‘is zero’, or ‘is greater than £10k’.
2. A set of rules. Also known as the rules engine. It’s the rules that describe the relationship between the IF and the THEN statements. For example a rule might be “IF a loan applicant has an income of zero THEN refuse the loan”.

Machine learning:-----------
Machine learning is an alternative approach which can help to address some of the issues with rules-based methods. Rather than attempt to fully emulate the decision process of an expert or best practice, machine learning methods typically only take the outcomes from the experts.

For example an insurance specialist may review a number of cases and decide whether they are fraudulent or not. Exactly how the expert arrived at their decision is not important for machine learning, only what their decision was. Focusing on the outcomes rather then entire decision making process can make machine learning more flexible and less susceptible to some of the problems encountered with rules-based systems.