https://github.com/thecoderpinar/mohs-hardness-ensemble-prediction

Mohs Hardness Prediction Project | Ensemble Models with Neural Networks, LGBM, CAT, XGB using a Voting Mechanism. 🚀💎
https://github.com/thecoderpinar/mohs-hardness-ensemble-prediction

Last synced: about 1 year ago
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Mohs Hardness Prediction Project | Ensemble Models with Neural Networks, LGBM, CAT, XGB using a Voting Mechanism. 🚀💎

• Host: GitHub
• URL: https://github.com/thecoderpinar/mohs-hardness-ensemble-prediction
• Owner: ThecoderPinar
• License: mit
• Created: 2023-11-20T12:55:43.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2024-02-03T21:39:21.000Z (about 2 years ago)
• Last Synced: 2025-02-09T04:16:12.117Z (about 1 year ago)
• Language: Jupyter Notebook
• Size: 14.2 MB
• Stars: 0
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Mohs Hardness Ensemble Prediction

> A collaborative project utilizing ensemble models for predicting Mohs hardness. 🚀💎

---

## Table of Contents

- [Description](#description)

- [Models](#models)

- [Installation](#installation)

- [Usage](#usage)

- [Contributing](#contributing)

- [License](#license)

---

## Description

This project focuses on predicting Mohs hardness using a combination of various machine learning models. The ensemble includes Neural Networks, LGBM, CAT, and XGB, all working together through a Voting Mechanism. The goal is to create a robust and accurate prediction system for Mohs hardness.

---

## Models

- Neural Networks

- LightGBM (LGBM)

- CatBoost (CAT)

- XGBoost (XGB)

---

## Installation

```bash

# Clone the repository

git clone https://github.com/ThecoderPinar/mohs-hardness-ensemble-prediction.git

# Navigate to the project directory

cd mohs-hardness-ensemble-prediction

# Install dependencies

pip install -r requirements.txt

# Usage

To run the prediction models, follow these steps:

- Open the Jupyter Notebook or Python script.

- Run the cells or execute the script.

- Input the relevant features for prediction.

- Obtain the predicted Mohs hardness.

# Contributing

- Fork the project (https://github.com/ThecoderPinar/mohs-hardness-ensemble-prediction/fork)

- Create your feature branch (git checkout -b feature/AmazingFeature)

- Commit your changes (git commit -am 'Add some AmazingFeature')

- Push to the branch (git push origin feature/AmazingFeature)

Open a pull request

# License

Distributed under the MIT License. See LICENSE for more information.

# Contact

Pinar Topuz - piinartp@gmail.com

Project Link: https://github.com/ThecoderPinar/mohs-hardness-ensemble-prediction