Net-Net Auto Machine Learning (AutoML) Prediction of Complex Ecosystems.

ABSTRACT: Biological Ecosystem Networks (BENs) are webs of biological species (nodes) establishing trophic relationships (links). Experimental confirmation of all possible links is difficult and generates a huge volume of information. Consequently, computational prediction becomes an important goal. Artificial Neural Networks (ANNs) are Machine Learning (ML) algorithms that may be used to predict BENs, using as input Shannon entropy information measures (Shk) of known ecosystems to train them. However, it is difficult to select a priori which ANN topology will have a higher accuracy. Interestingly, Auto Machine Learning (AutoML) methods focus on the automatic selection of the more efficient ML algorithms for specific problems. In this work, a preliminary study of a new approach to AutoML selection o

SUBMITTER: Barreiro E 

PROVIDER: S-EPMC6098100 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature