My doubt was "where does Maxent take that value from?".
I didn't know if the Initial Loss is the entropy of environmental layer values at all landscape, at occurrence points or at background points. I calculated these entropies in R and the Initial Loss corresponds to entropy of environmental layer values at background points.
I'm also not an expert in Machine Learning and algorithms... The information gain is based on the decrease in entropy after a dataset is split on an attribute, right? So, in Maxent, the gain is calculated by:
Gain = entropy after iterarions - entropy before iterations
Is that right? If that is, following the definition of Gain from the Maxent help:
Gain = log of the number of grid cells - log loss (average of the negative log probabilities of the sample locations)
So...
Log of the number of grid cells = entropy before iterations = entropy of background points
Log loss (average of the negative log probabilities of the sample locations) = entropy of model after iterations
Is that right?