Create a raw fuzzy system containing only two rules.
fis=CreateSystemWith2Rules(InTrain,OutTrain);
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Parameters
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InTrain - matrix containing the input values of the training data
points. Each row corresponds to a data point, each column
corresponds to an input dimension.
OutTrain - column vector containing the output values of the training
data points. Each row corresponds to a data point.
CreateOptions - column vector containing parameters of the system generation
(1) Coefficient for the core
(2) Coefficient for the support
(3) Apply or not meta rule 1.
(4) Coefficient for dmin in meta rule 1.
(5) Apply or not meta rule 2.
(6) Coefficient for dpmin in meta rule 2.
(7) Enable a part of the shape of the linguistic terms to fall
outside the range of the linguistic variable.
(8) Number of allowed decimals for set parameters.
CreateOptions - vector describing the preferences
1 - DecimalsNo - Number of allowed decimals. Defines the precision.
2 - CoreRelWidth - Width of the core of the new sets
relative to the range of the
linguistic variable.
3 - SupportRelWidth - Width of the support of the new sets
relative to the range of the
linguistic variable.
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Returned values
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fis - complex structure describing the raw Fuzzy Inference System.
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Remarks
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The two rules aim the description of the minimum and maximum output.
First one seeks the two extreme output values and a representative data
point for each of them. If several data points correspond to an extreme
value, one selects the one that is closer to an endpoint of the input
domain.
The reference points of the antecedent sets of the first rule will be
identical with the corresponding input values of the minimum point.
The reference point of the consequent set will be identical with the
output value of the minimum point. The shape of the linguistic terms is
determined by the default set shape, which is a characteristic feature
of the dimension. The antecedent and consequent linguistic terms of the
second rule are determined in a similar way taking into consideration
the maximum point.
At this point the system contains two linguistic terms in each dimension.
This version of the function supports only trapezoid shaped fuzzy sets.
In order to fulfill the conditions related to trapezoid sets, the
widths of the cores and supports are shrunk the same amount if it is
necessary. However, their reference points are kept always unmodified.
In case of a coincidence in any of the dimensions the sets are unified
and only the first specified set is kept.
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Zsolt Csaba Johanyák, johanyak.csaba@gamf.kefo.hu, v. 1.2, 27 Aug 2007.