Background
Methods
The CBR classifier with plasma proteomic profiles
Prior studies for weight optimization
Authors | Year | Methods | Weights |
---|---|---|---|
Cardie & Howe [14] | (1997) | Information gain | G(f) a |
Ahn & Kim [12] | (2009) | Relative importance [0-7] |
\( \frac{x_f}{\sum \limits_{f=1}^m{x}_f} \)
|
Gu et al. [13] | (2010) | Delphi method | – |
Chang et al. [5] | (2011) | Delphi method | – |
Zhao et al. [7] | (2011) | Entropy method |
\( \frac{entropy_f}{\sum \limits_{f=1}^m{entropy}_f} \)
|
Liang et al. [8] | (2012) | Logistic regression |
\( \frac{Wald_f}{\sum \limits_{f=1}^m{Wald}_f} \)
|
Rank-based weight optimization
Distance functions and problem setting
Conversion to rank-order information
Weight optimization
Application and experiments
Features (Abbreviation) | Type | Contents |
---|---|---|
Initial Response (IR) | Binary number | 0: decreasing |
1: increasing | ||
Temperature 1 (T1) | Real number | Range [45 - 55] |
Temperature 2 (T2) | Real number | Range [56 - 90] |
Maximum Peak at T1 (PEAK1) | Real number | Range [0 - ∞] |
Maximum Peak at T2 (PEAK2) | Real number | Range [0 - ∞] |
A set of individual ∆C
p
(IND) | A vector of real numbers | Range [0 - ∞] |
Results
Fold | Model | IR | PEAK1 | PEAK2 | T1 | T2 | IND |
---|---|---|---|---|---|---|---|
I | ETCBR | 0.0067 | 0.0145 | 0.0347 | 0.0595 | 0.0220 | 0.8625 |
LWCBR | 0.0158 | 0.1145 | 0.3845 | 0.0960 | 0.0179 | 0.3713 | |
RWCBR | 0.1704 | 0.1890 | 0.1488 | 0.1886 | 0.1596 | 0.1436 | |
II | ETCBR | 0.0089 | 0.0311 | 0.0477 | 0.0766 | 0.0314 | 0.8042 |
LWCBR | 0.0877 | 0.0752 | 0.2550 | 0.0016 | 0.3244 | 0.2561 | |
RWCBR | 0.2190 | 0.2222 | 0.0954 | 0.2203 | 0.1325 | 0.1106 | |
III | ETCBR | 0.0068 | 0.0265 | 0.0391 | 0.0654 | 0.0243 | 0.8377 |
LWCBR | 0.0175 | 0.1780 | 0.2481 | 0.1188 | 0.1584 | 0.2793 | |
RWCBR | 0.1274 | 0.2603 | 0.1144 | 0.2837 | 0.1092 | 0.1051 | |
IV | ETCBR | 0.0076 | 0.0259 | 0.0383 | 0.0643 | 0.0247 | 0.8392 |
LWCBR | 0.0001 | 0.3524 | 0.0682 | 0.4252 | 0.1484 | 0.0056 | |
RWCBR | 0.1627 | 0.2266 | 0.1279 | 0.2206 | 0.1233 | 0.1388 | |
V | ETCBR | 0.0065 | 0.0223 | 0.0345 | 0.0581 | 0.0213 | 0.8573 |
LWCBR | 0.0250 | 0.0036 | 0.1628 | 0.2751 | 0.3219 | 0.2116 | |
RWCBR | 0.2205 | 0.2186 | 0.1024 | 0.2334 | 0.1076 | 0.1175 |
Fold | Measures | K-NN | SVM | SCUCC | CLCBR | ETCBR | LWCBR | RWCBR |
---|---|---|---|---|---|---|---|---|
I | Precision | 0.5000 | 0.8571 | 1.0000 | 0.6667 | 1.0000 | 0.8000 | 1.0000 |
Recall | 0.7143 | 0.8571 | 0.2857 | 0.5714 | 0.7143 | 0.5714 | 0.7143 | |
F1-score | 0.5882 | 0.8571 | 0.4444 | 0.6154 | 0.8333 | 0.6667 | 0.8333 | |
G-measure | 0.5976 | 0.8571 | 0.5345 | 0.6171 | 0.8452 | 0.6761 | 0.8452 | |
II | Precision | 0.8571 | 0.8571 | 1.0000 | 0.8000 | 0.7500 | 0.3333 | 1.0000 |
Recall | 0.8571 | 0.8571 | 0.8571 | 0.5714 | 0.8571 | 0.2857 | 0.8571 | |
F1-score | 0.8571 | 0.8571 | 0.9231 | 0.6667 | 0.8000 | 0.3077 | 0.9231 | |
G-measure | 0.8571 | 0.8571 | 0.9258 | 0.6761 | 0.8018 | 0.3086 | 0.9258 | |
III | Precision | 0.6000 | 0.8571 | 0.8333 | 0.7500 | 0.8333 | 0.7778 | 0.7778 |
Recall | 0.8571 | 0.8571 | 0.7143 | 0.8571 | 0.7143 | 1.0000 | 1.0000 | |
F1-score | 0.7059 | 0.8571 | 0.7692 | 0.8000 | 0.7692 | 0.8750 | 0.8750 | |
G-measure | 0.7171 | 0.8571 | 0.7715 | 0.8018 | 0.7715 | 0.8819 | 0.8819 | |
IV | Precision | 0.7500 | 1.0000 | 1.0000 | 1.0000 | 0.8750 | 0.7778 | 1.0000 |
Recall | 0.8571 | 1.0000 | 0.5714 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | |
F1-score | 0.8000 | 1.0000 | 0.7273 | 1.0000 | 0.9333 | 0.8750 | 1.0000 | |
G-measure | 0.8018 | 1.0000 | 0.7559 | 1.0000 | 0.9354 | 0.8819 | 1.0000 | |
V | Precision | 0.5455 | 0.8571 | 0.7000 | 0.6000 | 1.0000 | 0.6000 | 0.7778 |
Recall | 0.8571 | 0.8571 | 1.0000 | 0.8571 | 1.0000 | 0.8571 | 1.0000 | |
F1-score | 0.6667 | 0.8571 | 0.8235 | 0.7059 | 1.0000 | 0.7059 | 0.8750 | |
G-measure | 0.6838 | 0.8571 | 0.8366 | 0.7171 | 1.0000 | 0.7171 | 0.8819 |
Measures | Statistics | K-NN | SVM | SCUCC | CLCBR | ETCBR | LWCBR | RWCBR |
---|---|---|---|---|---|---|---|---|
Precision | MIN | 0.5000 | 0.8571 | 0.7000 | 0.6000 | 0.7500 | 0.3333 | 0.7778 |
AVG | 0.6506 | 0.8857 | 0.9067 | 0.7633 | 0.8917 | 0.6578 | 0.9111 | |
STD | 0.1490 | 0.0639 | 0.1362 | 0.1529 | 0.1087 | 0.1985 | 0.1217 | |
MAX | 0.8571 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 0.8000 | 1.0000 | |
Recall | MIN | 0.7143 | 0.8571 | 0.2857 | 0.5714 | 0.7143 | 0.2857 | 0.7143 |
AVG | 0.8285 | 0.8857 | 0.6857 | 0.7714 | 0.8571 | 0.7428 | 0.9143 | |
STD | 0.0639 | 0.0639 | 0.2748 | 0.1917 | 0.1429 | 0.3097 | 0.1278 | |
MAX | 0.8571 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | |
F1-score | MIN | 0.5882 | 0.8571 | 0.4444 | 0.6154 | 0.7692 | 0.3077 | 0.8333 |
AVG | 0.7236 | 0.8857 | 0.7375 | 0.7576 | 0.8672 | 0.6861 | 0.9013 | |
STD | 0.1067 | 0.0639 | 0.1795 | 0.1514 | 0.0965 | 0.2320 | 0.0637 | |
MAX | 0.8571 | 1.0000 | 0.9231 | 1.0000 | 1.0000 | 0.8750 | 1.0000 | |
G-measure | MIN | 0.5976 | 0.8571 | 0.5345 | 0.6171 | 0.7715 | 0.3086 | 0.8452 |
AVG | 0.7221 | 0.8857 | 0.7649 | 0.7624 | 0.8708 | 0.6931 | 0.9070 | |
STD | 0.1088 | 0.0639 | 0.1451 | 0.1488 | 0.0951 | 0.2345 | 0.0593 | |
MAX | 0.8571 | 1.0000 | 0.9258 | 1.0000 | 1.0000 | 0.8819 | 1.0000 |