I'm working on comparing 2 algorithms with an experimental protocol that produce 100 folds for each one.
As a result, I found that my algorithm got (49.29 $\pm$ 1.69) and the baseline got (50.40 $\pm$ 2.16). I applied ANOVA and other tests and I always got a p-value of 0.60.
Method: Deep learning.
Goal: comparing 2 algorithms (mine and another)
Field: computer-vision
Hypothesis ($\alpha=0.05$):
- $H_0$: the mean of the results are equal.
- $H_a$: the mean of the results are unequal. (advantage go to the adversary)
Results:
$mean_{proposed}$ < $mean_{baseline}$
Population: 2 ( proposed and baseline)
sample size = 100
$P=0.6$ and $\alpha = 0.05$
$P > 0.05 $ $=>$ no significant difference
My conclusion : the 2 algorithms are equal.
Can a reviewer reject my conclusion (my fail to reject the H0)?
How can I defend my point of view?
If you need more information, please ask them in a comment.