public class RSFSS
extends java.lang.Object
RSFSS is the model to be obtained as the regression model using the fuzzy random sets regression algorithm. Detailed in: L. Sánchez. A Random Sets-Based Method for Identifying Fuzzy Models. Fuzzy Sets and Systems 98:3 (1998) 343-354.
Constructor and Description |
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RSFSS(double[][] pX,
double[] pY)
Class constructor.
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Modifier and Type | Method and Description |
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double[] |
getOutput(double[] x)
This methods returns a evaluation of the given example using all the clusters found.
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void |
RSFSSX2(int NC,
Randomize r,
double sigma)
This methods carries out the modelling algorithm based on Random Sets FSS 2000 using
lables for the clusters.
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void |
RSFSSX3(int NC,
Randomize r,
double sigma)
This methods carries out the modelling algorithm based on Random Sets FSS 2000 without using
lables for the clusters.
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public RSFSS(double[][] pX, double[] pY)
Class constructor.
pX
- the input data from the dataset as a bi-dimensional double arraypY
- the output data from the dataset as an array of doublespublic void RSFSSX3(int NC, Randomize r, double sigma)
This methods carries out the modelling algorithm based on Random Sets FSS 2000 without using lables for the clusters.
NC
- an integer with the number of clusters to generater
- a Randomize objectsigma
- a double value with the sigmoide value for the centres membership functionspublic double[] getOutput(double[] x)
This methods returns a evaluation of the given example using all the clusters found.
x
- the example for which its membership degreee is to be evaluatedpublic void RSFSSX2(int NC, Randomize r, double sigma)
This methods carries out the modelling algorithm based on Random Sets FSS 2000 using lables for the clusters.
NC
- an integer with the number of clusters to generater
- a Randomize objectsigma
- a double value with the sigmoide value for the centres membership functions