Scholarly Works per year
Scholarly Works per year
Description
A .py file containing all python code used in analyzing data. Specifically machine learning methods of logistic regression and support vector machine.
| Date made available | 2020 |
|---|---|
| Publisher | The Royal Society |
Research output
- 1 Article
-
Branching principles of animal and plant networks identified by combining extensive data, machine learning and modelling: Branching principles of animal and plant networks identified by combining extensive data, machine learning and modelling
Brummer, A. B., Lymperopoulos, P., Shen, J., Tekin, E., Bentley, L. P., Buzzard, V., Gray, A., Oliveras, I., Enquist, B. J. & Savage, V. M., Jan 2021, In: Journal of the Royal Society Interface. 18, 174, 20200624.Research output: Contribution to journal › Article › peer-review
Open Access9 Scopus citations