IMPROVE
Contents:
What is the IMPROVE project?
Background
Future Directions
Acknowledgments
Publications
Contact Us
Installation
Quickstart
User Guide
Running a Single Model
Curating New Models
Curating Steps
Requirements for Curated Models
Step-by-Step Example
Preprocessing Script Example
Training Script Example
Inference Script Example
Configuration Example
Templates
Preprocessing
Training
Inference
Model Parameters
Config File
Readme
Download Scripts
Using Workflows
CSA
Brute-Force CSA
Scaling CSA
Swarm CSA
Post-process CSA Results
HPO
DeepHyper HPO
LCA
Generate LCA Splits
Brute-Force LCA
Swarm LCA
Post-process LCA Results
Using Non-Benchmark Data
Applications
Drug Response Prediction
Problem Formulation
Benchmark Data
Models
LGBM
XGBoost-DRP
RandomForest-DRP
DeepCDR
GraphDRP
HiDRA
tCNNS
Uno
DeepTTC
DualGCN
IGTD
PaccMann-MCA
PathDSP
Synergy
Problem Formulation
Benchmark Data
Models
Matchmaker
DeepDDS
IMPROVE API Reference
Parameters
Preprocess
Train
Infer
Creating Model-Specific Parameters
Configuration Files
improvelib.utils
get_response_data
get_x_data
get_response_with_features
get_features_in_response
determine_transform
transform_data
build_ml_data_file_name
save_stage_ydf
build_model_path
store_predictions_df
compute_performance_scores
get_common_samples
get_common_elements
Timer
improvelib.metrics
compute_metrics
mse
rmse
pearson
spearman
r_square
acc
bacc
kappa
f1
precision
recall
roc_auc
aupr
Developer Guide
Creating a Workflow
Creating an Application
Release Notes
v0.1.0
v0.0.3
Branch Naming
IMPROVE
IMPROVE API Reference
IMPROVE Parameters
View page source
IMPROVE Parameters
Preprocess
Train
Infer
Creating Model-Specific Parameters
Configuration Files
Version: latest
Versions
latest
v0.1.0
v0.0.3-beta