Explaining anomalies detected by autoencoders using Shapley Additive Explanations

Towards explaining anomalies: A deep Taylor decomposition of one-class models

(2020) Jacob Kauffmann et al.   PATTERN RECOGNITION

Anomaly explanation with random forests

(2020) Martin Kopp et al.   EXPERT SYSTEMS WITH APPLICATIONS

Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI

(2019) Alejandro Barredo Arrieta et al.   Information Fusion

Situ: Identifying and Explaining Suspicious Behavior in Networks

(2018) John R. Goodall et al.   IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS

Peeking inside the black-box: A survey on Explainable Artificial Intelligence (XAI)

(2018) Amina Adadi et al.   IEEE Access

Explanation in artificial intelligence: Insights from the social sciences

(2018) Tim Miller   ARTIFICIAL INTELLIGENCE

Optimal classification trees

(2017) Dimitris Bertsimas et al.   MACHINE LEARNING

Evaluating the Visualization of What a Deep Neural Network Has Learned

(2017) Wojciech Samek et al.   IEEE Transactions on Neural Networks and Learning Systems

A Hybrid Semi-Supervised Anomaly Detection Model for High-Dimensional Data

(2017) Hongchao Song et al.   Computational Intelligence and Neuroscience

High-dimensional and large-scale anomaly detection using a linear one-class SVM with deep learning

(2016) Sarah M. Erfani et al.   PATTERN RECOGNITION

A review of instance selection methods

(2010) J. Arturo Olvera-López et al.   ARTIFICIAL INTELLIGENCE REVIEW

Anomaly detection

(2009) Varun Chandola et al.   ACM COMPUTING SURVEYS

Explaining instance classifications with interactions of subsets of feature values

(2009) E. Štrumbelj et al.   DATA & KNOWLEDGE ENGINEERING