Progress Indication for Machine Learning Model Building: A Feasibility Demonstration

Area of Science:

• Computer Science
• Machine Learning

Background:

• Machine learning model building is time-consuming.
• Progress indicators are needed to estimate remaining time and completion.
• A prior framework lacked detailed implementation.

Purpose of the Study:

• To demonstrate the viability of progress indicators for machine learning.
• To provide detailed implementation techniques for progress indicators.

Main Methods:

• Developed implementation techniques for progress indicators.
• Focused on three major supervised machine learning algorithms.
• Implemented techniques within the Weka software.

Main Results:

• Successfully demonstrated the feasibility of progress indicators.
• Provided concrete implementation details for supervised learning.
• Showcased practical application in Weka.

Conclusions:

• Progress indicators for machine learning model building are feasible.
• Detailed techniques enable practical implementation.
• This work bridges the gap between framework and application.