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It is natural to come up with two different phylogenetic trees and thus classifications of a specific taxon if the analysis was based exclusively on adults, larvae, eggs, or even on the composition of all stages.
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Consequently it is necessary to take into account these technical errors for a binary classification of a specific nucleotide.
If classification of a specific dataset yields low error rates (defined later), the objective of the odd-ball paradigm was considered to be fulfilled.
Diagnosis and classification to a specific type of shock.
Dependent variables (1) Blood pressure, MAP, heart rate, respiratory rate, oxygen saturation at time 0, 30min, 60min, 90min and 120min after arrival (2) Blood lactate, pH, PaCO2, base excess and bicarbonate levels on arrival (3) Diagnosis and classification to a specific type of shock (4) Immediate survival to hospital admission (5) Short-term survival at 30 days .
Both of the adopted FS methods measure the classification capability of a specific feature with respect to a two-class problem.
Now, we obtain a stability region for the additional DMU within which, in addition to efficiency classification, the efficiency score of a specific inefficient DMU is preserved.
Furthermore, this study determines a stability region for the additional DMU within which, in addition to efficiency classification, the efficiency score of a specific inefficient DMU is preserved and also using a simulation method, a region in which some specific efficient DMUs become inefficient is provided.
In fact, molecular classification of cancer is a specific classification problem, as it incorporates essential double implications: classification and identifying biomarkers of cancer.
We illustrate this approach to brain state classification using a specific instance of disease state prediction by successfully predicting whether any given subject was prenatally exposed to cocaine when no significant behavioral differences were found between the two groups.
Wrapper approaches use a given classification algorithm for the evaluation of a specific subset of features by training and testing it with cross-validation.
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