ML Paradigms on English AI Terms Dictionary

Semi-supervised learning

Sat, 18 Jul 2026 10:15:05 +0000

Definition

Semi-supervised learning is a hybrid training paradigm that utilizes a small amount of labeled data alongside a large volume of unlabeled data. The core assumption is that the structure of the unlabeled data can help define decision boundaries more effectively than labeled data alone. Techniques such as self-training, co-training, and graph-based methods are commonly used. This approach is valuable when labeling data is expensive or time-consuming, allowing models to achieve performance close to fully supervised methods with significantly fewer labeled examples.

Online

Sat, 18 Jul 2026 09:35:02 +0000

Definition

Online learning is a machine learning paradigm where the model is updated incrementally as new data points arrive, rather than being trained on a static batch of data all at once. This approach is crucial for applications dealing with streaming data, such as stock market predictions or real-time fraud detection. It allows systems to adapt quickly to changing patterns and distributions over time, ensuring that the model remains relevant and accurate in dynamic environments without requiring significant computational resources for full retraining.