ReliefF and SVM Example

Version 1.0.1 (3.22 MB) by Frederik D
Example of using ReliefF (Matlab: relieff) and SVM (Matlab: fitcsvm) for the classification of pharmaceutical pellets.
273 Downloads
Updated 28 Dec 2020

This repository was created for anybody interested in using feature selection (ReliefF, Matlab: relieff) and support vector machines (SVM, Matlab: fitcsvm) as a minimum working example to reproduce steps described in the publication below (Doerr2020). Data is provided in the sub-folder '_Data'. Structural features were extracted from micro-X-ray tomography data. ReliefF and SVM were used to build a classifier for the detection of broken pharmaceutical pellets within the sample.

Input Data:
(1) Extracted features of six ibuprofen (IBU) capsules (1763 pellets, 206 features):
'Desc_DataFile_C0.csv'
'Desc_DataFile_C1.csv'
'Desc_DataFile_C2.csv'
'Desc_DataFile_C3.csv'
'Desc_DataFile_C4.csv'
'Desc_DataFile_C5.csv'

(2) User defined feature categories:
'Feature_Categories.csv'

(3) Results of a feature sensitivity analysis:
'Feature_SenAnlys_Score.csv'

%------------------------------------------------------------------------------------------------
% Code written by Frederik Doerr, Feb 2020 (MATLAB R2019b)
% Application: For 'Support Vector Machine - Introduction and Application'

% % % Reference (open access):
% Doerr, F. J. S., Florence, A. J. (2020)
% A micro-XRT image analysis and machine learning methodology for the characterisation of multi-particulate capsule formulations.
% International Journal of Pharmaceutics: X.
% https://doi.org/10.1016/j.ijpx.2020.100041
% Data repository: https://doi.org/10.15129/e5d22969-77d4-46a8-83b8-818b50d8ff45
% Video Abstract: https://strathprints.strath.ac.uk/id/eprint/71463
%------------------------------------------------------------------------------------------------

Cite As

Doerr, Frederik J. S., and Alastair J. Florence. “A Micro-XRT Image Analysis and Machine Learning Methodology for the Characterisation of Multi-Particulate Capsule Formulations.” International Journal of Pharmaceutics: X, vol. 2, Elsevier BV, Dec. 2020, p. 100041, doi:10.1016/j.ijpx.2020.100041.

View more styles
MATLAB Release Compatibility
Created with R2019b
Compatible with any release
Platform Compatibility
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Versions that use the GitHub default branch cannot be downloaded

Version Published Release Notes
1.0.1

Minor corrections in description, references

1.0.0

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.