Files

script

updated feature interaction

Jun 21, 2019

ebac6a8 · Jun 21, 2019

Name		Name	Last commit message	Last commit date
parent directory ..
1.Filter_GBIF_records_from_SQL_database.ipynb		1.Filter_GBIF_records_from_SQL_database.ipynb	updated scripts and markdown data_gis_extended	Jun 18, 2019
2.Environmental_raster_layers.ipynb		2.Environmental_raster_layers.ipynb	updated feature interaction	Jun 21, 2019
3.Create_species_and_global_prediction_dataframes.ipynb		3.Create_species_and_global_prediction_dataframes.ipynb	updated scripts and markdown data_gis_extended	Jun 18, 2019
4.Train_DNN.ipynb		4.Train_DNN.ipynb	updated scripts and markdown data_gis_extended	Jun 18, 2019
5.Global_predictions_trained_DNN.ipynb		5.Global_predictions_trained_DNN.ipynb	updated feature interaction	Jun 21, 2019
README.md		README.md	updated readme files data_extended and data_GIS_extended	Jun 19, 2019
filtered.csv		filtered.csv	updated feature interaction	Jun 21, 2019

README.md

The scripts were used in the following order:

GBIF records were filtered.
The environmental variables were rasterized and stacked.
Species and global prediction dataframes were generated.
A DNN was trained to predict the probability of species occurrence for the training set of presence & pseudo-absences.
The trained DNN was used to predict the species potential global distribution.