Statistical significance testing (P-value Analysis) of the performance improvements achieved by the proposed hybrid model over state-of-the-art machine learning models. A statistical comparison was done on all major performance indicators of each comparative model. The p-values which are obtained as a result of relevant statistical tests support the idea that the observed better performance of the hybrid model is statistically significant (p < 0.05 of all comparisons and most p-values < 0.005). This strict comparison confirms the fact that the improvement of the performance is not caused by mere coincidence but a direct consequence of the effectiveness of the proposed framework.

Statistical significance testing (P-value Analysis) of the performance improvements achieved by the proposed hybrid model over state-of-the-art machine learning models. A statistical comparison was done on all major performance indicators of each comparative model. The p-values which are obtained as a result of relevant statistical tests support the idea that the observed better performance of the hybrid model is statistically significant (p < 0.05 of all comparisons and most p-values < 0.005). This strict comparison confirms the fact that the improvement of the performance is not caused by mere coincidence but a direct consequence of the effectiveness of the proposed framework.