3D FcRM modelling in miles per gallon of cars
The new fuzzy c-regression modeling (FcRM) are widely used in order to fit switching regression models. Minimization of objective function yields immediate estimates for different c regression models. The functions of model, estimation technique and results are discussed in this paper. A case st...
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| Main Authors: | , , |
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| Format: | Book Section |
| Language: | English |
| Published: |
Penerbit UTM
2008
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/14283/1/RobiahAdnan2008_3DFcRMModellinginMilesPerGallon.pdf http://eprints.utm.my/id/eprint/14283/ |
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| Summary: | The new fuzzy c-regression modeling (FcRM) are widely used in order to fit switching regression models. Minimization of objective function yields immediate estimates for different c regression models. The functions of model, estimation technique and results are discussed in this paper. A case study in miles per gallon (MPG) of different cars using the FcRM modeling was carried out. The 3D graph for significant independent variables for FcRM clustering is shown in this study. The comparison between multiple linear regression and FcRM modeling were done. The mean square error (MSE) was used to find the better model. It was found that the FcRM modeling with lower MSE to be the better model and has great capability in predicting the dependent variable effectively. |
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