May 2018
Beginner to intermediate
384 pages
10h 19m
English
book
Artificial Intelligence for Big Data
by Anand Deshpande, Manish Kumar, Albenzo Coletta, Giancarlo Zaccone
Content preview from Artificial Intelligence for Big Data
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Fuzzification
Digital computers are designed and programmed to primarily work with crisp sets. This means they are able to apply logical operations and computational reasoning based on the classical sets. In order to make intelligent machines, we require a process called fuzzification. With this process, the digital inputs are translated into fuzzy sets.
Membership of the fuzzy sets corresponds to a certain degree of certainty for the fuzzy set. Fuzzification is a process by which we move gradually from precise symbols to vagueness for the element representations, which translates measured numerical values into fuzzy linguistic values. Consider a set of numbers that are close to integer value 5:
Aclassic = {3,4,5,6,7}
Afuzzy = {0.6/2, 0.8/3, ...
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