https://github.com/muthu-kumar-u/ml-cluster-model

The ml-cluster-model repository contains an experimental K-Means clustering model for research purposes. It partitions data into clusters based on feature similarity. Currently unstable and unoptimized for accuracy, it is not recommended for production use.
https://github.com/muthu-kumar-u/ml-cluster-model

clustering fastapi kmeans-clustering machine-learning ml

Last synced: 4 months ago
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The ml-cluster-model repository contains an experimental K-Means clustering model for research purposes. It partitions data into clusters based on feature similarity. Currently unstable and unoptimized for accuracy, it is not recommended for production use.

• Host: GitHub
• URL: https://github.com/muthu-kumar-u/ml-cluster-model
• Owner: muthu-kumar-u
• License: mit
• Created: 2024-12-20T13:18:38.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2025-01-01T13:17:23.000Z (over 1 year ago)
• Last Synced: 2025-04-07T01:11:21.425Z (about 1 year ago)
• Topics: clustering, fastapi, kmeans-clustering, machine-learning, ml
• Language: Jupyter Notebook
• Homepage:
• Size: 289 KB
• Stars: 2
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Clustering Model

## Overview

This repository contains an experimental machine learning clustering model developed using the K-Means algorithm. The model partitions data into clusters based on feature similarity, aiming to identify inherent groupings within the dataset. Currently, the model is in an unstable state and has not been optimized for accuracy. It is intended for research purposes and is not recommended for production use.

## Pre-trained Model

A pre-trained version of the clustering model is available in the `model.pkl` file. This file can be used to apply the clustering algorithm to new datasets. Please note that due to the model's current instability, results may vary, and further optimization is required for improved accuracy.

## Requirements

To run the model, ensure you have the following dependencies installed:

- Python 3.10 or higher

- Required Python packages (listed in `requirements.txt`)

## Setup Instructions

1. **Fork the Repository:**

   To use this repository, you first need to fork it into your own GitHub account. You can then clone it locally to make changes.

   ```bash

   git clone 

2. **Set Up the Environment:**

   

   ```bash

   python -m venv venv

   source venv/bin/activate  # On Windows, use `venv\Scripts\activate`

2. **Install Dependencies:**

   

   ```bash

   pip install -r requirements.txt

## Important note:

   * This repository comes with a pre-trained K-Means model with the dataset. If you want more accuracy, please re-train the model with a cleaner dataset and perform feature engineering on the model.