Gestalt: integrated support for implementation and analysis in machine learning

We present Gestalt, a development environment designed to support the process of applying machine learning. While traditional programming environments focus on source code, we explicitly support both code and data. Gestalt allows developers to implement a classification pipeline, analyze data as it moves through that pipeline, and easily transition between implementation and analysis. An experiment shows this significantly improves the ability of developers to find and fix bugs in machine learning systems. Our discussion of Gestalt and our experimental observations provide new insight into general-purpose support for the machine learning process. Author Keywords Gestalt, machine learning, software development. ACM Classification Keywords H5.2 Information Interfaces and Presentation: User Interfaces; D2.6 Programming Environments: Integrated Environments.

• Type: Journal
• Year: 2010
• Where: UIST
• Authors: Kayur Patel, Naomi Bancroft, Steven M. Drucker, James Fogarty, Andrew J. Ko, James A. Landay
• Keywords: Machine, Programming Environments, Software Engineering, Traditional Programming Environments, UIST 2010