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ROE Evaluation BETA

This web based application enables automation of Rank Order Entropy utilizing Kendall Tau. This ROE process will examine an input dataset and give a recommendation for the user in terms of the stability of models created by the dataset. Datasets should be input as a comma- or tab-delimited file with activity at the right-most column. The procedure takes the dataset, divides it to training/testing sets, optimizes parameters for modeling, tests the training/testing sets for ability to model, and then models the data, and finally examines the data in terms of Rank Order and Rank Order Entropy.

When using this code, please cite the following paper: Rank Order Entropy

A tutorial for ROE analysis can be found here

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Procedural options - model method selection and dataset manipulation.
 
Data contains header
Does your top line contain labels for each descriptor or activity?
 
Data contains names
Does your left column contain labels for each entry?
 
Do not optimize using cousin threshhold (shortens run time)
Correlated descriptors (cousin descriptors) can be removed if this remains unchecked. Otherwise, all descriptors are used.
 
Verbose output (default is non-verbose with status bar)
Verbose output gives specific details of progress.
 
Number of random dataset splits
 
Do not optimize parameters; instead, use user-input parameters.
Reduces runtime if you know what are optimal parameters for your model. Recommended parameters are pre-selected.
 
Number of latent variables for PLS modeling:
 
Cousin threshhold for PLS modeling:
 
Number of latent variables for KPLS modeling:
 
Sigma value for KPLS modeling:
 
Cousin threshhold for KPLS modeling:
 
Provide your data file in comma- or tab-delimited format.
Do not use underscores or non-alphanumeric characters besides '.' in your file's name.
Response should be the last column. If in doubt, test your dataset in ROMS first.

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