Visus: An Interactive System for Automatic Machine Learning Model Building and Curation

07/05/2019
by   Aécio Santos, et al.
0

While the demand for machine learning (ML) applications is booming, there is a scarcity of data scientists capable of building such models. Automatic machine learning (AutoML) approaches have been proposed that help with this problem by synthesizing end-to-end ML data processing pipelines. However, these follow a best-effort approach and a user in the loop is necessary to curate and refine the derived pipelines. Since domain experts often have little or no expertise in machine learning, easy-to-use interactive interfaces that guide them throughout the model building process are necessary. In this paper, we present Visus, a system designed to support the model building process and curation of ML data processing pipelines generated by AutoML systems. We describe the framework used to ground our design choices and a usage scenario enabled by Visus. Finally, we discuss the feedback received in user testing sessions with domain experts.

READ FULL TEXT
research
05/06/2020

Testing the Robustness of AutoML Systems

Automated machine learning (AutoML) systems aim at finding the best mach...
research
04/16/2020

Developing and Deploying Machine Learning Pipelines against Real-Time Image Streams from the PACS

Executing machine learning (ML) pipelines on radiology images is hard du...
research
06/21/2023

Automated Machine Learning for Remaining Useful Life Predictions

Being able to predict the remaining useful life (RUL) of an engineering ...
research
04/24/2020

Towards A Domain-Customized Automated Machine Learning Framework For Networks and Systems

Clouds gather a vast volume of telemetry from their networked systems wh...
research
03/03/2018

Towards Automatic & Personalised Mobile Health Interventions: An Interactive Machine Learning Perspective

Machine learning (ML) is the fastest growing field in computer science a...
research
07/28/2023

FeedbackLogs: Recording and Incorporating Stakeholder Feedback into Machine Learning Pipelines

Even though machine learning (ML) pipelines affect an increasing array o...
research
06/14/2023

Accelerating Machine Learning Queries with Linear Algebra Query Processing

The rapid growth of large-scale machine learning (ML) models has led num...

Please sign up or login with your details

Forgot password? Click here to reset