Deep Inference of Personality Traits by Integrating Image and Word Use in Social Networks
Table 3: Classification accuracies (%) for each personality trait on the Mindpics dataset
['[BOLD] Model', '[BOLD] O', '[BOLD] C', '[BOLD] E', '[BOLD] A', '[BOLD] N', '[BOLD] Avg']
The first two rows show the performance of the Alexnet model trained from scratch with random weights initialization. The first row shows the results obtained by training an independent model for each trait, and the second row the results obtained by training just one model that shares most of the computation and that has an independent output layer for each trait. As it can be seen in the table, the all-in-one model obtains better accuracies in all the traits except for Agreeableness, and the average accuracy is 0.5 % better compared to training five independent models.