Predicting Young Imposter Syndrome Using Ensemble Learning

Table 3

Feature importance scores obtained for the features of the young imposter syndrome dataset employing neural network and random forest model.

Feature	Neural network	Random forest
Y7	1.435915476	0.060705199
Y2	0.848385469	0.162305453
Y5	0.758418731	0.042913745
Y4	0.729478374	0.012774768
Y6	0.566908382	0.064326011
Y3	0.531113149	0.050292544
Y8	0.381514902	0.042809194
Reason for study choice (RSC)	0.076035131	0.002130504
Smoking status	0.031637418	−0.000818094
Y1	0.029711063	−0.000117368
Monthly family income (MFI)	0.026247537	−0.002682493
BMI	0.005986669	−0.000505573
Sex	0.00416312	−0.000420911
Age	−0.004779267	0.000966939
Living with family	−0.024055834	0.001383877
Academic year (AY)	−0.045372056	0.001460318