by instadatahelp | Sep 1, 2023 | AI Blogs
Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application to Credit-Risk Evaluation Cynthia Rudin, Yaron Shaposhnik; 24(16):1−44, 2023. Abstract This study presents a novel method for comprehending specific predictions made by global...
![Combining Deep Inductive Logic Programming with Reinforcement Learning (arXiv:2308.16210v1 [cs.LG])](https://instadatanews.com/wp-content/uploads/2023/08/arxiv-logo-fb-1080x675.png)
by instadatahelp | Sep 1, 2023 | AI Blogs
One way to explain the hierarchical levels of understanding in a machine learning model is through the use of inductive logic programming (ILP), which is a data efficient approach capable of learning logical rules that can capture data behavior. A variation of ILP,...
by instadatahelp | Sep 1, 2023 | AI Blogs
Contrasting Identifying Assumptions of Average Causal Effects: Robustness and Semiparametric Efficiency Tetiana Gorbach, Xavier de Luna, Juha Karvanen, Ingeborg Waernbaum; 24(197):1−65, 2023. Abstract This paper examines different identifying assumptions for...
by instadatahelp | Sep 1, 2023 | AI Blogs
The content can be rewritten as: Emotion recognition using electroencephalogram (EEG) encompasses two main scenarios: classifying discrete labels and regressing continuously tagged labels. While numerous algorithms have been proposed for classification tasks, there...
by instadatahelp | Sep 1, 2023 | AI Blogs
Interpolating Classifiers with Few Mistakes Tengyuan Liang and Benjamin Recht; 24(20):1−27, 2023. Abstract This paper presents a basic analysis of the regret and generalization capabilities of minimum-norm interpolating classifiers (MNIC). MNIC is a function that...
