SVM and kNN exemplify several important trade-offs in machine learning (ML). SVM is often less computationally demanding than kNN and is easier to interpret, but it can identify only a limited set ...

To a large extent, supervised ML is for domains where automated machine learning does not perform well enough. Scientists add supervision to bring the performance up to an acceptable level.

The support vector machine (SVM) is known for its good performance in two-class classification, but its extension to multiclass classification is still an ongoing research issue. In this article, we ...

Machine-learning algorithms find and apply patterns in data. And they pretty much run the world.

This study employed machine learning – support vector machines (SVM) – to determine whether such structures can be automatically extracted from LiDAR data and classified using computerised techniques.

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...