Table 1 The precision of the combinations of various classifiers and feature reduction algorithms.
From: Context based mixture model for cell phase identification in automated fluorescence microscopy
classifier | FR algorithm | Precision (confidence Interval) (at 90% confidence level) | |||
|---|---|---|---|---|---|
| Â | Â | class 1 | class 2 | class 3 | class 4 |
CBMM | PCA | 0.9129 (0.8824,0.9433) | 0.8683 (0.7723,0.9643) | 0.9412 (0.9055,0.9770) | 0.8586 (0.8011,0.9160) |
| Â | LDA | 0.9021 (0.8786,0.9758) | 0.8614 (0.8010,0.9218) | 0.9496 (0.9432,0.9756) | 0.8536 (0.8172,0.8900) |
| Â | MMC | 0.9170 (0.8850,0.9490) | 0.8417 (0.7253,0.9581) | 0.9354 (0.8973,0.9734) | 0.8022 (0.7672,0.8371) |
| Â | SDAFS | 0.8487 (0.8064,0.8910) | 0.7967 (0.7023,0.8906) | 0.9484 (0.9048,0.9920) | 0.8700 (0.8244,0.9156) |
| Â | MIFS | 0.7902 (0.7449,0.8357) | 0.7633 (0.6735,0.8531) | 0.9483 (0.9204,0.9761) | 0.8783 (0.8208,0.9358) |
| Â | GA | 0.8556 (0.823,0.8883) | 0.7833 (0.6584,0.9083) | 0.9642 (0.9336,0.9947) | 0.8881 (0.8422,0.9340) |
SVM | PCA | 0.9200 (0.9022,0.9375) | 0.7518 (0.7045,0.7991) | 0.9088 (0.8896,0.9279) | 0.8069 (0.7721,0.8417) |
| Â | LDA | 0.9969 (0.9911,1.0026) | 0 (0,0) | 0.8840 (0.8487,0.9193) | 0 (0,0) |
| Â | MMC | 0.9216 (0.9119,0.9314) | 0.6655 (0.5946,0.7363) | 0.8960 (0.8724,0.9195) | 0.7190 (0.6670,0.7681) |
| Â | SDAFS | 0.9457 (0.9372,0.9542) | 0.6018 (0.5409,0.6627) | 0.9214 (0.9059,0.9369) | 0.8048 (0.7501,0.8596) |
| Â | MIFS | 0.9457 (0.9257,0.9656) | 0.6454 (0.5438,0.7470) | 0.9086 (0.8819,0.9353) | 0.8401 (0.7913,0.8888) |
| Â | GA | 0.9381 (0.9194,0.9568) | 0.7827 (0.7173,0.8481) | 0.9172 (0.8902,0.9441) | 0.8396 (0.7930,0.8661) |
KNN | PCA | 0.9487 (0.9349,0.9625) | 0.6691 (0.5927,0.7455) | 0.9215 (0.8977,0.9454) | 0.7588 (0.7167,0.8001) |
| Â | LDA | 0.7313 (0.6975,0.7652) | 0.2773 (0.2005,0.3541) | 0.2144 (0.1767,0.2520) | 0.0922 (0.0605,0.1238) |
| Â | MMC | 0.9532 (0.9367,0.9699) | 0.6327 (0.5570,0.7084) | 0.9171 (0.8984,0.9360) | 0.7387 (0.6764,0.8010) |
| Â | SDAFS | 0.9487 (0.9393,0.9582) | 0.5110 (0.4324,0.5895) | 0.9150 (0.8831,0.9469) | 0.7908 (0.7541,0.8275) |
| Â | MIFS | 0.9532 (0.9376,0.9689) | 0.5518 (0.4832,0.6204) | 0.9087 (0.8932,0.9242) | 0.8040 (0.7732,0.8347) |
| Â | GA | 0.9668 (0.9481,0.9856) | 0.6273 (0.5469,0.7077) | 0.9384 (0.9276,0.9492) | 0.7841 (0.7420,0.8262) |
BPNN | PCA | 0.9004 (0.8707,0.9301) | 0.6817 (0.5352,0.8281) | 0.8876 (0.8369,0.9383) | 0.8106 (0.7669,0.8543) |
| Â | LDA | 0.8929 (0.8513,0.9345) | 0.0100 (0.000,0.0283) | 0.7746 (0.6147,0.9345) | 0.2644 (0.1050,0.4238) |
| Â | MMC | 0.8960 (0.8758,0.9162) | 0.4664 (0.2381,0.6947) | 0.8895 (0.8501,0.9289) | 0.5919 (0.4672,0.7167) |
| Â | SDAFS | 0.7472 (0.5156,0.978) | 0.3364 (0.1228,0.5499) | 0.7279 (0.5048,0.9509) | 0.7032 (0.5559,0.8506) |
| Â | MIFS | 0.8351 (0.6638,1.000) | 0.4882 (0.2847,0.6917) | 0.7342 (0.5084,0.9599) | 0.7687 (0.608,0.9294) |
| Â | GA | 0.7872 (0.6192,0.9552) | 0.3791 (0.1147,0.6435) | 0.7234 (0.5007,0.9461) | 0.7341 (0.5679,0.9003) |