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A radically different approach of dealing with the uncertainty than the traditional probabilistic and the statistical methods. The necessary feature of the fuzzy set is a membership function which assigns the grade of membership between 0 and 1 to each and every member of the set.
Mathematically the membership function of a fuzzy set A is a mapping from a space χ to unit interval As the memberships take their values in the unit interval, it is appealing to think of them as probabilities; though, memberships do not follow the laws of probability and it is possible to permit an object to simultaneously hold the nonzero degrees of membership in sets traditionally considered to be mutually exclusive.
The methods which are derived from the theory have been proposed as an alternatives to traditional statistical methods in areas like quality linear regression, control and forecasting, though they have not met with the universal acceptance and a number of statisticians have commented that they could not found any solution using such an approach which could not have been achieved as least as effectively using the probability and statistics.
Machine learning is a term which literally means the ability of a machine to recognize patterns which have occurred repetitively and to improve its performance based on the past
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Knox's tests: These tests designed to detect any tendency for the patients with a particular disease to form the disease cluster in time and space. The tests are relied on a two-b
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The Null Hypothesis - H0: There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1: There is heteroscedasticity i.e. β 1 0 Reject H0 if Q = ESS/2 >
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