/WekaLogFileAnalysis

WekaLogFileAnalysis is a user-friendly tool designed to convert Weka log files into detailed learning graphs, facilitating the visual assessment and comparison of machine learning model performances. Perfect for educators, researchers, and data scientists seeking to enhance their analysis with graphical insights.

Primary LanguageJupyter NotebookMIT LicenseMIT

Weka Log File Analyisis

3D plotting coming soon...

Overview

This project is designed to assist researchers, data scientists, and educators in analyzing Weka log files through visual representations. By uploading a Weka log file, users can easily generate learning graphs that visualize the performance and progression of machine learning models. This tool aims to simplify the analysis process, making it more accessible and understandable for individuals regardless of their technical background.

Purpose

The primary purpose of this project is to provide a user-friendly interface for generating learning graphs from Weka log files. These graphs can help users quickly assess the effectiveness of different algorithms, understand the learning rate of models, and make informed decisions about model adjustments for improved performance.

How to Use

Open In Colab

To get started with generating your learning graphs, follow the simple steps below:

Step 1: Open the Project in Google Colab

  • Click on the "Open In Colab" button above to navigate directly to the Google Colab project.
  • Ensure you're logged into your Google account to access and run the project.

Step 2: Upload Your Weka Log File

  • In the Colab interface, find the cell that contains the upload file code snippet.
  • Run this cell, and you will be prompted to select and upload your Weka log file from your computer.
  • The file will be automatically processed to prepare it for graph generation.

Step 3: Generate Learning Graphs

  • Scroll to the section of the Colab notebook that contains cells for generating different types of learning graphs.
  • Run the cells corresponding to the graphs you wish to generate. Each cell is labeled with the type of graph it produces (e.g., Accuracy over Time, Error Rates).
  • The graphs will be displayed directly within the Colab notebook once the cells have executed successfully.