Table 5.
Performance comparison of recent prediction models on various Lung Cancer datasets
Work Ref. | Classifier | Performance Metrics | |||||
---|---|---|---|---|---|---|---|
ACC | P | R | F1 | Error | AUC | ||
UCI -TSD Dataset | |||||||
Danjuma [47] | MLP | 0.82 | 0.82 | 0.82 | 0.82 | – | 0.84 |
MLCD Dataset | |||||||
Murty et al. [151] | RBF-NN | – | – | – | – | 0.19 | – |
UCI-Irvine Dataset | |||||||
Patra [161] | RBF-NN | 0.81 | 0.81 | 0.81 | 0.81 | – | 0.75 |
Dey et al. [49] | LAGOA+RF | 0.86 | – | – | – | – | – |
LCD Dataset | |||||||
Radhika et al. [169] | SVM | 0.99 | – | – | – | – | – |
Salaken et al. [183] | Deep-ANN | 0.80 | – | – | – | – | – |
Maleki et al. [132] | Deep-ANN | 1.00 | – | – | – | – | – |
SEER Dataset | |||||||
Ali and Reza [180] | RIPPER with AdaBoost | 0.89 | – | – | – | – | 0.95 |
Doppalapudi et al. [53] | ANN | 0.71 | 0.71 | 0.71 | 0.71 | – | 0.87 |
SLCD Dataset | |||||||
Nasser and Abu-Naser [153] | ANN | 0.97 | – | – | – | – | – |