This repository contains the trained models and datasets for the paper 

"Machine Learning Classification of Trajectories from Molecular Dynamics Simulations of Chromosome Segregation"
(submitted but not yet accepted).

The results listed in the paper can be reproduced with the data and trained models stored here. 
The code to be used for this can be found in the github repository https://github.com/DavidGeisel/ML_Classification_MD_Trajectories.

To reproduce the results, the Github repository should be cloned into a local folder as
/home/.../git_repo/

Thereafter, the data stored in this repo should be copied into 
/home/.../git_repo/ML-models/

The results of the nested cross-validation analyses for the classifiers should be stored into
/home/.../git_repo/ML-models/nested-cross-validation
Within this directory, the data and trained classifiers for the nested cross-validation analyses are to be found in the respective subdirectories as
ML-models/nested-cross-validation/<classifier>/<input dimension>/

The data types stored in this repo consist of the following files:
- .npy (= numpy arrays, can be loaded with numpy.load() in python)
- .joblib (= trained ML models, can be loaded with joblib.load() in python)

For every iteration of the nested cross-validation (denoted by Version number "V_") the trained model and the corresponding train and test sets are provided
- X_train_V_....npy
- X_test_V_...npy
- y_train_binary_V_...npy
- y_test_binary_V_...npy
- <CLF>_V_...joblib