MLF-GUI

A web-based graphical user interface for managing and monitoring machine learning workflows with medical time-series data. This application provides an interface for configuring data processing pipelines, training models, performing classification tasks, and visualizing results.

Features

• Process Management: Configure and monitor machine learning workflows including data preprocessing, feature selection, model training, and evaluation
• Data Exploration: Interactive dataset viewer and analysis tools
• Classification: Perform time-series classification with real-time progress tracking
• Results Visualization: View and analyze training metrics, evaluation results, and model performance
• Live Monitoring: Real-time process logs and status updates

Project Structure

• packages/frontend/ - React-based web interface built with Vite, TanStack Router, and Radix UI
• packages/backend/ - Express.js server with tRPC API for process management and Python integration
• packages/core/ - Shared types and utilities

Getting Started

Prerequisites

• Node.js (v18 or higher)
• pnpm package manager
• Python (v3.8 or higher)

Installation

1. Install dependencies:

   pnpm install

2. Set up Python environment (if needed for backend processing)

Running the Application

Start both frontend and backend in development mode:

pnpm dev

This will start:

• Frontend: http://localhost:5173
• Backend: http://localhost:3000

You can also run them separately:

• Frontend only: pnpm dev:frontend
• Backend only: pnpm dev:backend