Implement Fuzzy
Logic
In
Boolean or two valued logic the truth values of a variable will always be
either 0 or 1 and in traditional two-valued set theory , one element belongs to
the set or not.
Similar
to this in typical Classification problem, an observation is classified into
one of several different classes . In all of these case there is a definitive true value.
Fuzzy
logic presents a different approach to these problems
, In fuzzy logic the truth values of a variable or the label (in a classification problem) is a real
number between 0 and 1.
The
word Fuzzy means hazy, blured, confeaed and not clear.
When
it comes to binary logic the statement is either True or False 1 or 0.
On
a pleasant summer day the statement “ temperature is too high”
It
means that the real world is too complicated for precise description of certain
situations, therefore fuzziness must be introduced in order to get n traceable
and reasonable model.
It
means there is no certainity and it all depends on the content.
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