Redirigiendo al acceso original de articulo en 16 segundos...
Inicio  /  Information  /  Vol: 13 Par: 10 (2022)  /  Artículo
ARTÍCULO
TITULO

Constructing Explainable Classifiers from the Start?Enabling Human-in-the Loop Machine Learning

Vladimir Estivill-Castro    
Eugene Gilmore and René Hexel    

Resumen

Interactive machine learning (IML) enables the incorporation of human expertise because the human participates in the construction of the learned model. Moreover, with human-in-the-loop machine learning (HITL-ML), the human experts drive the learning, and they can steer the learning objective not only for accuracy but perhaps for characterisation and discrimination rules, where separating one class from others is the primary objective. Moreover, this interaction enables humans to explore and gain insights into the dataset as well as validate the learned models. Validation requires transparency and interpretable classifiers. The huge relevance of understandable classification has been recently emphasised for many applications under the banner of explainable artificial intelligence (XAI). We use parallel coordinates to deploy an IML system that enables the visualisation of decision tree classifiers but also the generation of interpretable splits beyond parallel axis splits. Moreover, we show that characterisation and discrimination rules are also well communicated using parallel coordinates. In particular, we report results from the largest usability study of a IML system, confirming the merits of our approach.

 Artículos similares

       
 
Soe Thandar Aung, Nobuo Funabiki, Lynn Htet Aung, Safira Adine Kinari, Mustika Mentari and Khaing Hsu Wai    
The Flutter framework with Dart programming allows developers to effortlessly build applications for both web and mobile from a single codebase. It enables efficient conversions to native codes for mobile apps and optimized JavaScript for web browsers. S... ver más
Revista: Information

 
Hellena Hempe, Alexander Bigalke and Mattias Paul Heinrich    
Background: Degenerative spinal pathologies are highly prevalent among the elderly population. Timely diagnosis of osteoporotic fractures and other degenerative deformities enables proactive measures to mitigate the risk of severe back pain and disabilit... ver más
Revista: Information

 
Yu-Hung Chang, Chien-Hung Liu and Shingchern D. You    
The dynamic flexible job-shop problem (DFJSP) is a realistic and challenging problem that many production plants face. As the product line becomes more complex, the machines may suddenly break down or resume service, so we need a dynamic scheduling frame... ver más
Revista: Information

 
Yuhuan Wu and Yonghong Wu    
Salient object detection (SOD) aims to identify the most visually striking objects in a scene, simulating the function of the biological visual attention system. The attention mechanism in deep learning is commonly used as an enhancement strategy which e... ver más
Revista: Algorithms

 
Jiarui Xia and Yongshou Dai    
Ground roll noise suppression is a crucial step in processing deep pre-stack seismic data. Recently, supervised deep learning methods have gained popularity in this field due to their ability to adaptively learn and extract powerful features. However, th... ver más
Revista: Applied Sciences