From: A machine learning approach to predict perceptual decisions: an insight into face pareidolia
Subject | Classification performance of individual subjects (in %) | |||
---|---|---|---|---|
TFPS39 | TFPSL17 | TFPSR17 | DATFPS17 | |
p value: 0.035 | p value: 0.03 | p value: 0.035 | p value: 0.045 | |
Subject1 | \(69.98 \pm 6.11\) | \(66.92 \pm 6.70\) | \(63.80 \pm 6.19\) | \(\mathit{70 }.\mathit{05 } \pm \mathit{7 }.\mathit{16 }\) |
Subject2 | \(73.08 \pm 6.27\) | \(70.38 \pm 6.73\) | \(67.74 \pm 6.84\) | \(\mathit{73 }.\mathit{30 } \pm \mathit{6 }.\mathit{26 }\) |
Subject3 | \(\mathit{70 }.\mathit{67 } \pm \mathit{6 }.\mathit{57 }\) | \(65.81 \pm 6.56\) | \(62.69 \pm 5.45\) | \(69.74 \pm 6.76\) |
Subject4 | \(72.67 \pm 5.72\) | \(69.43 \pm 7.13\) | \(65.62 \pm 6.30\) | \(\mathit{74 }.\mathit{33 } \pm \mathit{6 }.\mathit{52 }\) |
Subject5 | \(69.86 \pm 6.83\) | \(65.58 \pm 6.84\) | \(68.17 \pm 6.76\) | \(\mathit{71 }.\mathit{03 } \pm \mathit{7 }.\mathit{16 }\) |
Subject6 | \(\mathit{75 }.\mathit{04 } \pm \mathit{5 }.\mathit{83 }\) | \(67.86 \pm 6.41\) | \(69.43 \pm 6.93\) | \(72.82 \pm 6.38\) |
Subject7 | \(71.93 \pm 6.24\) | \(65.92 \pm 6.07\) | \(68.17 \pm 6.34\) | \(\mathit{72 }.\mathit{92 } \pm \mathit{6 }.\mathit{56 }\) |
PAM | \(71.89 \pm 1.88\) | \(67.41 \pm 1.89\) | \(66.52 \pm 2.53\) | \(\mathit{72 }.\mathit{03 } \pm \mathit{1 }.\mathit{76 }\) |