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accuracy of classification
The example shows that the accuracy of classification systems of the fuzzy association rules is better than that of the two popular classification methods: C4.5 and CBA.
      
Moreover, the classification results of both methods are combined to improve the accuracy of classification.
      
The RD model can synthetically judge the quality of attribute data, which is different from other measurement coefficients that only discuss accuracy of classification.
      
We also show that certain metrics are dominant in their effects on classifying quality and that additional metrics are not needed to increase the accuracy of classification.
      
We also show that certain metrics are dominant in their effects on classifying quality and that additional metrics are not needed to increase the accuracy of classification.
      
A modification of Weber's analytical scheme is proposed, not merely to improve the accuracy of classification of legal orders but more importantly to permit empirical analysis of their dynamics.
      
Because ICADS TES does not need the support of a priori information of surface types, it is also not influenced by the accuracy of classification and the problem of mixture pixels.
      
The overall accuracy of classification was about 83.1% (MDC) and 82.6% (MLC) for group 1 and 76.4 (MDC) and 78.0% (MLC) for group 2, respectively.
      
By discriminant analysis, the overall accuracy of classification (into clinical grades 1, 2, 3 and normal) on the basis of MR was 65%.
      
This latter method was also compared to other classifiers (such as logistic regression and k nearest neighbours) with respect to its accuracy of classification.
      
In addition, four measures are presented in this paper for evaluating the accuracy of classification approaches to a wide range of traditional and multi-label classification problems.
      
Accuracy of classification was toward the low end of the range of published values, but was reasonable given the difficult nature of separating forest classes from satellite images.
      
The difference in the accuracy of classification with the spectrophotometer, the wavelength range as the explanatory variables, and the light-exposure condition of the sample were examined in detail.
      
The overall accuracy of classification of individual images by SPOT HRV-XS reached 56%, and TM 66%, while the fused data set provided accuracy of about 78%, which was raised to 81% after recoding by using DEM.
      
The validity of the predictive model to define the different groups was tested by assessing the accuracy of classification.
      
Contextual data can be incorporated, or 'fused', with spectral data to improve the accuracy of classification algorithms.
      
This strategy results in considerably higher accuracy of classification and better generalization as compared to previous neural network models.
      
Experimental results indicate that the accuracy of classification is maintained or even increased when the proposed method is applied for missing attribute value prediction.
      
The outcomes show that classifiers induced using the representation enriched by the GP-constructed features provide better accuracy of classification on the test set.
      
Moreover, the accuracy of classification was virtually identical when only the more heavily weighted checklist items were used.
      
 

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