Data Science Press
What are Fuzzy Algorithms,data science glossary,fuzzy logic examples,fuzzy set,fuzzy logic applications,fuzzy logic tutorial,advantages of fuzzy logic,fuzzy logic examples from real world,fuzzy logic for dummies,fuzzy logic in machine learning,data science glossary kaggle,data science keywords,data science in layman terms,data terminology and concepts,google data science glossary,data terminology definitions,data science definitions,data science phrases,

Data Science Glossary: What are Fuzzy Algorithms

Algorithms that use fuzzy logic to decrease the runtime of a script. Fuzzy algorithms tend to be less precise than those that use Boolean logic. They also tend to be faster, and computational speed sometimes outweighs the loss in precision.

In fuzzy mathematics, fuzzy logic is a form of many-valued logic in which the truth values of variables may be any real number between 0 and 1 both inclusive. It is employed to handle the concept of partial truth, where the truth value may range between completely true and completely false. The concept of fuzzy logic had been studied since the 1920’s. The term fuzzy logic was first used with 1965 by Lotfi Zadeh a professor of UC Berkeley in California. He observed that conventional computer logic was not capable of manipulating data representing subjective or unclear human ideas. Fuzzy logic has been applied to various fields, from control theory to AI. It was designed to allow the computer to determine the distinctions among data which is neither true nor false. Something similar to the process of human reasoning.

Data Science PR

Add comment

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Follow us

Don't be shy, get in touch. We love meeting interesting people and making new friends.