Contrastive learning is one of the fundamental paradigms for unsupervised 3-D skeleton-based action recognition. Existing contrastive learning paradigms typically enhance model discrimination by ...

Predictive data mining, often termed supervised data mining, involves predicting a predefined target variable based on input features. In contrast, descriptive data mining, also known as unsupervised ...

Article citations More>> Michael, W.B., Azlinah, M. and Bee, W.Y. (2019) Supervised and Unsupervised Learning for Data Science. Springer Nature, 47-128. has been cited by the following article: TITLE: ...

Supervised learning relies on historical, labeled data to train algorithms for specific outcomes. This approach is widely used in the financial sector, where reliable past data can guide future ...

This article explores the transformative potential of machine learning algorithms in combating supply chain fraud, focusing on techniques such as supervised and unsupervised learning, anomaly ...

Unsupervised learning approach improved prediction using all classification methods, emphasizing the impact of deploying subtype analysis to complex data. Conclusion: This research revealed that ...

What is data poisoning? AI/ML models are built on core training datasets that are continually updated through supervised and unsupervised learning.

1.Introduction This course offers a concise overview of the core theories and techniques in both Artificial Intelligence and Data Mining, emphasizing state space representation and search strategies, ...