BCAR was applied to Text Categrization. Below is the related paper.

Yoon, Y. and Lee, G. G. (2008). "Text categorization based on boosting association rules". In Proceedings of ICSC 2008, Second IEEE International Conference on Semantic Computing, pages 136-143. [pdf]

Prediction results of "unknown" data from SherLOC

The following link contains the file which lists the preiction results of subcellular localization using "unknown" data.


Prediction results of individual subcellular locations using MultiLOC data

The below table contains the prediction results for a redundant testset of MultiLOC plant data. There are three sets of results, each of which denotes the prediction result for the input sequences from the front, the center and the rear part in a primary sequence. Furthermore, each set is divided into the results for four different input sequence length.
length / partFrontCenterRear
50 residues front_c50 center_c50 rear_c50
100 residues front_c100 center_c100 rear_c100
300 residues front_c300 center_c300 rear_c300
500 residues front_c500 center_c500 rear_c500

Following table contains the prediction results for the redundancy-reduced testset. Remember that the prediction accuracy for the redundancy-reduced testset is lower than that for the redundant testset by more than 3% in average.
length / partFrontCenterRear
50 residues front_rr_c50 center_rr_c50 rear_rr_c50
100 residues front_rr_c100 center_rr_c100 rear_rr_c100
300 residues front_rr_c300 center_rr_c300 rear_rr_c300
500 residues front_rr_c500 center_rr_c500 rear_rr_c500

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Intelligent Software Laboratory, Defpt. of Computer Sci. & Eng., POSTECH