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Table 4: Averaged classification results showing Accuracy, Precision, Recall, NMI, and B-Cubed (NMI and B-Cubed values are not available for the linear combination of the two classifiers)

Table 4 Averaged classification results showing Accuracy, Precision, Recall, NMI, and B-Cubed (NMI and B-Cubed values are not available for the linear combination of the two classifiers)

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Algorithm 1. Event detection
Algorithm 1. Event detection
Table 1: Example for clustering Flickr pictures
Table 1: Example for clustering Flickr pictures
5.3 Results B-Cubed estimates the precision and recall associated with each document in the data set individually, and then uses the average precision P, and average recall Ry values for the data set to compute B-Cubed as:
5.3 Results B-Cubed estimates the precision and recall associated with each document in the data set individually, and then uses the average precision P, and average recall Ry values for the data set to compute B-Cubed as:
Figure 1: Classification results (Acc, P, R) for the experimental runs using only tags as features
Figure 1: Classification results (Acc, P, R) for the experimental runs using only tags as features
Table 6: Examples of best and worst performing (by Acc) classifiers for the different experimental runs
Table 6: Examples of best and worst performing (by Acc) classifiers for the different experimental runs
Related topics:
Machine LearningEvent DetectionUser Generated ContentMultimedia RetrievalImage SearchInformation NeedCollaborative Tagging
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