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The classification of units into ordinal categories of consumption used in the Welsh Health Survey dataset is based on the Department of Health definitions (Table 1) [ 42].
The dataset provided the classification of units into ordinal categories of maximal daily consumption based on the UK Department of Health definitions (table 1), with categories for 'none/never drinks', 'within guidelines', 'excess consumption but less than binge' and 'binge'binge
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The final trained model with the identification rule and criterion for the classification of flow units was used for identifying flow units in the cored and non-cored intervals of reservoir.
In this paper we deal with the problem of designing a classifier able to learn the classification of existing units in inventory and then use it to classify new units according to their attributes in a multi-criteria ABC inventory classification environment.
Table 2 presents a matrix of the units' profiles for the two practice environment factors and the resulting classification of the units for this dimension.
Table 3 presents a matrix of the units' profiles for the two indicators related to staffing and the resulting classification of the units for this dimension.
Table 2 presents a matrix of the units' profiles for the two actual scope of practice factors and the resulting classification of the units for this dimension.
Table 3 presents a matrix of the units' profiles for the five indicators related to capacity for innovation and the resulting classification of the units for this dimension.
The classification of distillation units has been done on the basis of literature survey till today.
It is concluded that using the combination of the WT and LSSVM improved the accuracy of classification of flow units in the Minghuazhen Formation.
The frame of businesses is highly heterogeneous in terms of size and industrial classification of its units, whereas the one associated with social surveys is more homogeneous.
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