Sentence examples for considering classification from inspiring English sources
The proposed approach is data driven without considering classification standard of different risk levels, and thus provides a more reasonable and objective result.
In contrast, considering classification tasks with similar degradations in the training and the evaluation set, non-invariant image descriptors have proven to be mostly quite effective [21].
In this section, performance of the proposed method is investigated considering classification accuracy obtained under different conditions, such as varying the feature dimension, utilizing different spectral bands for feature extraction and employing various types of kernel function in SVM classifier.
Therefore, we propose the comprehensive prediction model of drug side effect and its incidence using the data mining approach at the intersection of statics, machine learning and database system considering classification and regression characteristics of the side effect.
From the illustration, it is evident that, although both LBP 8,1 and CLBP _ S 8,1 _ M 8,1 exhibit better performance than other operators in the case of accurate detection of the normal case ('NOM'), LBP 8,1 is superior to CLBP_S 8,1 _M 8,1 while considering classification accuracy of the 'RUN' category.
Considering classification results on chemosensory genes (Figure 1) and on ABC transporter genes (Figure 2) together, we can see that certain programs tend to outperform others.
We consider classification techniques that are based on statistical and AI techniques.
The new policy would also permit reclassification of documents that have already been made public, and give the Central Intelligence Agency special authority to resist decisions by an interagency panel that considers classification appeals, typically from researchers.
In this paper, we show that wavelet performances in terms of classification accuracy can be pushed further by customizing them for the considered classification task.
If the pitches of melody and accompaniment are similar, we expect higher error rates for the considered classification tasks.
These properties of ICAMM are well-suited for the problem considered: classification of ceramic pieces coming from four different periods, namely, Bronze Age, Iberian, Roman, and Middle Ages.
