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However, most of them have only focused on classifying samples into nominal categories; thus, the unique characteristic of credit-rating – ordinality – seldom has been considered in the proposed approaches.
In the second part of the study the expert system was trained and adjusted on the basis of analytical data, and its reliability in classifying samples in different quality groups was tested.
In some discrimination methods, M-distance limits of 10 15 for maximum variance have been reported for classifying samples but threshold values vary according to the type of sample and application [44].
This illustrates the risks of combing data or classifying samples using existing data.
The refined signature still achieved 80% accuracy of classifying samples from mixed cancer types.
An unbiased estimate ("out of bag", based on samples not used to fit the tree) of error rate for classifying samples to one of four groups is 16%.
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Based on the linear separability of the classifying sample, the sample is classified by the suitable classifier.
First, we classified samples according to sampling year and viral subtype, and then performed a Chi-squared analysis for trends.
In the output layer of the network, the softmax classifier is applied to classify samples.
This maximizes the classifier's ability to classify samples accurately.
Consequently, the optimal number of hardest-to-classify samples can improve the classifier efficiency.
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