https://github.com/marta-barea/visnir-waxtype-classification-ml

Spectroscopic data processing approaches for petroleum wax discrimination
https://github.com/marta-barea/visnir-waxtype-classification-ml

cheminformatics chemistry chemoinformatics machine-learning petroleum r vis-nir-spectroscopy

Last synced: 21 days ago
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Spectroscopic data processing approaches for petroleum wax discrimination

• Host: GitHub
• URL: https://github.com/marta-barea/visnir-waxtype-classification-ml
• Owner: Marta-Barea
• License: gpl-3.0
• Created: 2022-04-22T08:40:08.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2024-11-20T17:37:56.000Z (about 1 month ago)
• Last Synced: 2024-11-20T18:27:36.904Z (about 1 month ago)
• Topics: cheminformatics, chemistry, chemoinformatics, machine-learning, petroleum, r, vis-nir-spectroscopy
• Language: R
• Homepage:
• Size: 1.92 MB
• Stars: 2
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Rapid Classification of Petroleum Waxes: A Vis-NIR Spectroscopy and Machine Learning Approach

## Description

This repository contains the source code for all data processing and the application of machine learning algorithms used in the article "Rapid Classification of Petroleum Waxes: A Vis-NIR Spectroscopy and Machine Learning Approach".

---

## 📂 Repository Structure

- `spectra/`: Folder containing the spectra data.

- `supervised algorithms/`: Source code for all the supervised machine learning models and experiments.

- `unsupervised algorithms/`: Source code related to unsupervised learning techniques and clustering.

- `App/`: A Shiny application to demonstrate and visualize the findings.

## 🛠️ **System Requirements**

### Software

- **R version 4.2.0** 

- RStudio (optional but recommended)

### Packages

- **prospectr (version 0.2.3)**: Used for calculating the first derivative for each sample spectrum with the `savitzkyGolay` function.

- **stats (version 4.1.2)**: Utilized for HCA with the `hclust` function, PCA with the `prcomp` function, and one-way ANOVA with the `aov` function.

- **cluster (version 2.1.2)**: Linkage method selection for the HCA established using the `agnes` function.

- **factoextra (version 1.0.7)**: Used for visualizing HCA results with the `fviz_dend` function and for extracting and visualizing the PCA result with the `fviz_eig` function.

- **ggplot2 (version 3.3.5)**: Employed for plotting the scores and loadings of the PCA with the `ggplot` function and generating the spectralprint radar chart.

- **caret (version 6.0-90)**: Utilized for developing the SVM and RF models.

- **graphics (version 4.1.2)**: The `filled.contour` function was used to generate the contour plot for the SVM model.

- **ggiraphExtra (version 0.3.0)**: Assisted in generating the spectralprint radar chart.

- **shiny (version 1.7.1)**: Utilized for developing the web application.

## ⚙️ How to Use This Repository

### Clone the Repository

   
 ```bash

                         git clone https://github.com/Marta-Barea/visnir-waxtype-classification-ml

                         cd visnir-waxtype-classification-ml 


### Running the Shiny Application

1. Place `app.R`, `svm.rds`, `svr.rds`and `test_data.xlsx` in the same folder.

2. In your R console, run: 

   

   
 ```R 

                         shiny::runApp("app.R") 


3. Use the web interface to:

- 📁 **Upload** `.csv` or `.xlsx` data files.

- 🛠️ **Preprocess** data using advanced filtering techniques.

- 🤖 **Predict** wax type with AI.

---

### 📂 **Example Dataset**

A sample dataset (`test_data.xlsx`) is included for demonstration purposes. It contains Vis-NIR spectral readings and hydroprocessing grades for various wax samples.

---

### 🤝 **Contributors**

- **University of Cádiz (AGR-291 Research Group)**

  - Specializing in hydrocarbon characterization and spectroscopy.

---

### 📜 **License**

This project is licensed under the GNU GENERAL PUBLIC License. See `LICENSE` for details.