Table 3.
Masking | (dis)similarity parameter | |||||
---|---|---|---|---|---|---|
Pearson (s) | MI (s) | NMI (s) | HKL (d) | L1norm (d) | L2norm2 (d) | |
α | 0.15 | 0.02 | 0.02 | − 0.07 | 0.25 | 0.22 |
β | 0.38 | 0.56 | 0.5 | 0.45 | − 0.04 | − 0.09 |
γ | 0.4 | 0.6 | 0.51 | − 0.02 | 0.07 | 0.09 |
MI mutual information, NMI normalised mutual information, HKL Kullback–Leibler divergence, L1Norm L1 norm or Manhattan norm, L2norm2 square L2 norm or square Euclidean distance, (s) similarity parameter, (d) dissimilarity parameter (data are rounded to two significant digits, the highest correlation coefficient is emphasized in bold text)