Sentence examples for representative classification from inspiring English sources
In Table 1, several standard classification performance measures are shown, such as the representative classification accuracy (Acc)., the true positive rate (TPR), false positive rate (FPR), specificity, sensitivity and the area under the receiver operating characteristic curve (AUC).
During training, it is important to present learning examples with a known outcome (i.e. 'true' normal and 'true' glaucoma cases) and with all disease stages in order for the MLC to create representative classification decision boundaries.
This enables us to make more representative classifications, as it might happen that a user 'A' always speaks very fast and loudly, while a user 'B' always speaks in a very relaxed way.
In this study, we introduce seven representative multiclass classification techniques, classic and more recent, their rationale, advantages, disadvantages and a practical R code to implement them.
According to published data [4, 33, 34], the selected elements can be considered as representative for classification purposes.
Most of the data algorithms can be described by Fig. 4 in which it also shows that the representative algorithms clustering, classification, association rules, and sequential patterns will apply these operators to find the hidden information from the raw data.
A series of 10 CSD cases, broadly representative of the classification system, were selected and sufficient radiographic and clinical history to enable classification were assembled.
The considered approaches fall into three highly representative categories: clustering, classification and spectral mixture analysis.
The Weka algorithms are selected to be representative of regression, classification, and clustering algorithms.
They are implemented in conjunction with a classifier to find a set of highly representative features for classification tasks.
Then, the threshold value of each adjacent class is determined, namely the classification representative value (e(i)), which is determined as per the following principles (Zhao 2001): left.
