Summary of Explainable Algorithms for Machine Learning Models

Summary of Explainable Algorithms for Machine Learning Models

Click the "Xiaobai Learns Vision" above, select to add "Star" or "Top" Heavy content delivered to you first Summary of Model Explainability Introduction Currently, many machine learning models can make very good predictions, but they do not explain how they make these predictions well. Many data scientists find it difficult to understand why an algorithm … Read more

Introduction to Explainable Machine Learning Methods

1. Concept Machine learning is an important branch of artificial intelligence, focusing on improving the performance of computer systems or algorithms through learning from experience data to adapt to various environments and tasks. As machine learning becomes increasingly integrated into everyday life and widely applied, people are becoming more reliant on the critical decisions made … Read more

ShapeFormer: Shapelet Transformer for Multivariate Time Series Classification

ShapeFormer: Shapelet Transformer for Multivariate Time Series Classification

Source: Time Series Research This article is approximately 3400 words long and is recommended for a 5-minute read. This article introduces the Transformer in multivariate time series classification. Multivariate time series classification (MTSC) has attracted extensive research attention due to its diverse real-world applications. Recently, utilizing Transformers for MTSC has achieved state-of-the-art performance. However, existing … Read more