Metadata-Version: 2.1
Name: wdl-rf
Version: 0.0.15
Summary: Create molecular fingerprint features of Ligands and predicting Bioactivities Acting with G Protein-coupled Receptors
Home-page: UNKNOWN
Author: xhj,zqm
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.5
Description-Content-Type: text/markdown
Requires-Dist: autograd (>=1.3)
Requires-Dist: numpy (>=1.18.5)
Requires-Dist: pandas (>=1.0.5)
Requires-Dist: scipy (>=1.2.1)
Requires-Dist: scikit-learn (>=0.23.1)

# wdl_rf  
A two-stage algorithm WDL-RF allows end-to-end learning of prediction pipelines whose inputs are of arbitrary size, which contains the molecular fingerprint generation stage through a new weighted deep learning method and the bioactivity prediction stage by the random forest model.   



