Skip to main content
Figure 3 | BMC Bioinformatics

Figure 3

From: A multiresolution approach to automated classification of protein subcellular location images

Figure 3

Pictorial representation of classification accuracy results. The diagram shows results from Table 1 for those sets involving T3, namely (T3), (T3, M) and (T3, M, Z). Diamond markers represent the nMR system (no MR block), circles represent the MRB system (MR bases, no redundancy) and squares represent the MRF system (MR frames, redundancy). Filled markers denote the closed-form weighting algorithm (CF), while empty ones denote the open-form weighting algorithm (OF). The following trends are noteworthy: (a) Introducing MR (both MRB and MRF) significantly outperforms nMR, thus demonstrating that classifying in MR subspaces indeed improves classification accuracy. (b) MRF outperform MRB. (b) For the two versions of the weighting algorithm, open form and closed form, the closed-form algorithm slightly outperforms the open-form one. (d) The trend in each case is almost flat across various feature set combinations, indicating that the texture set T3 alone (26 features) is sufficient for high classification accuracy.

Back to article page