| dc.description.abstract | Our research is distributed into the following stages:
A. The production of a "ready for analysis" data set with attributes of a location or area listed in
each row together with the matching occurrence counts. We assembled data from many
sources, choose the appropriate level of aggregation (such as area size), and included
fabricated 0 counts.
B. Using machine learning algorithms such as linear regression, support vector regression,
random forests, etc., analyze this data set to produce predictive models. Additionally, this
section aims to provide light on the characteristics/features that are crucial for predicting the
presence/absence of a species.
C. Reviewing the developed models. | |
