| Author Summary | We then apply an ensemble of various machine learning algorithms to infer environmental and cellular information such as strain, growth phase, medium, oxygen level, antibiotic and carbon source. |
| Inference of missing phase information using iterative learning | Inference is based on consensus-based approach of four machine learning methods described above. |
| Introduction | As such, efficient training of machine learning methods is hindered due to data complexity, compatibility and the curse of dimensionality that plagues datasets with thousands of features (genes) but only a few samples (conditions). |
| Supporting Information | In each iteration, the phase of all samples that were originally unannotated is predicted, based on an ensample of 4 machine learning methods (Naive Bayes, SVM, Decision Tree, KNN) that produce a consensus outcome, as described in the Methods section of the manuscript. |