NICHE: A Curated Dataset of Engineered Machine Learning Projects in Python
Machine learning (ML) has gained much attention and been incorporated into our daily lives. While there are numerous publicly available ML projects on open source platforms such as GitHub, there have been limited attempts in filtering those projects to curate ML projects of high quality. The limited availability of such high-quality dataset poses an obstacle in understanding ML projects. To help clear this obstacle, we present NICHE, a manually labelled dataset consisting of 572 ML projects. Based on evidences of good software engineering practices, we label 441 of these projects as engineered and 131 as non-engineered. This dataset can help researchers understand the practices that are followed in high-quality ML projects. It can also be used as a benchmark for classifiers designed to identify engineered ML projects.
Mon 15 MayDisplayed time zone: Hobart change
11:00 - 11:45 | SE for MLData and Tool Showcase Track / Technical Papers at Meeting Room 110 Chair(s): Sarah Nadi University of Alberta | ||
11:00 12mTalk | AutoML from Software Engineering Perspective: Landscapes and ChallengesDistinguished Paper Award Technical Papers Chao Wang Peking University, Zhenpeng Chen University College London, UK, Minghui Zhou Peking University Pre-print | ||
11:12 12mTalk | Characterizing and Understanding Software Security Vulnerabilities in Machine Learning Libraries Technical Papers Nima Shiri Harzevili York University, Jiho Shin York University, Junjie Wang Institute of Software at Chinese Academy of Sciences; University of Chinese Academy of Sciences, Song Wang York University, Nachiappan Nagappan Facebook | ||
11:24 6mTalk | DeepScenario: An Open Driving Scenario Dataset for Autonomous Driving System Testing Data and Tool Showcase Track Chengjie Lu Simula Research Laboratory and University of Oslo, Tao Yue Simula Research Laboratory, Shaukat Ali Simula Research Laboratory Pre-print | ||
11:30 6mTalk | NICHE: A Curated Dataset of Engineered Machine Learning Projects in Python Data and Tool Showcase Track Ratnadira Widyasari Singapore Management University, Singapore, Zhou Yang Singapore Management University, Ferdian Thung Singapore Management University, Sheng Qin Sim Singapore Management University, Singapore, Fiona Wee Singapore Management University, Singapore, Camellia Lok Singapore Management University, Singapore, Jack Phan Singapore Management University, Singapore, Haodi Qi Singapore Management University, Singapore, Constance Tan Singapore Management University, Singapore, Qijin Tay Singapore Management University, Singapore, David Lo Singapore Management University | ||
11:36 6mTalk | PTMTorrent: A Dataset for Mining Open-source Pre-trained Model Packages Data and Tool Showcase Track Wenxin Jiang Purdue University, Nicholas Synovic Loyola University Chicago, Purvish Jajal Purdue University, Taylor R. Schorlemmer Purdue University, Arav Tewari Purdue University, Bhavesh Pareek Purdue University, George K. Thiruvathukal Loyola University Chicago and Argonne National Laboratory, James C. Davis Purdue University Pre-print | ||