Academia.eduAcademia.edu

Figure 5 – uploaded by Mihai Paiu

See full PDFdownloadDownload figure
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 Figures (6)

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:
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)
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
Related topics:
Machine LearningEvent DetectionUser Generated ContentMultimedia RetrievalImage SearchInformation NeedCollaborative Tagging
580 California St., Suite 400
San Francisco, CA, 94104
© 2025 Academia. All rights reserved