One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine ...

This month, we look at two very common supervised methods in the context of ... exemplify several important trade-offs in machine learning (ML). SVM is often less computationally demanding than ...

Interestingly, the study also identified a counterintuitive negative association between heavy alcohol consumption and ...

SVM is a machine-learning set of algorithms that can be used to predict ... While this is not yet a foolproof method of predicting earthquakes, it is a promising step forward in our efforts to better ...

Long-read sequencing technologies analyze long, continuous stretches of DNA. These methods have the potential to improve ...

Machine learning is a branch of artificial ... and Support Vector Machine (SVM). You can also use ensemble methods (combinations of models), such as Random Forest, other Bagging methods, and ...

Understanding how cities grow is vital for shaping sustainable urban futures—but mapping the true extent of urban expansion ...

A scientist in Sweden has developed a new hybrid local features-based method using thermographs ... “Shallow classifiers, such as support vector machine (SVM), train the model on the feature ...

The team is further developing additional methods that are also computationally fast and yet can further enhance the accuracy of risk scores through more advanced modeling. "Some of the existing ...