Multi-label classification deals with problem domains in which each instance belongs to more than one class simultaneously. Label Powerset (LP) is an efficient multi-label learning algorithm that ...

Class imbalance is a common problem in machine learning, where some classes are overrepresented or underrepresented in the training data. This can lead to poor performance, bias, and unfairness in ...

Classes are sometimes called as targets/ labels or categories. Topics random-forest naive-bayes classification artificial-neural-networks decision-trees k-nearest-neighbours ...

On the Label categories page, specify a set of classes to categorize your data.. Your labelers' accuracy and speed are affected by their ability to choose among classes. For instance, instead of ...

Class-conditional noise commonly exists in machine learning tasks, where the class label is corrupted with a probability depending on its ground-truth. Many research efforts have been made to improve ...

The rapid development of deep learning in recent years is largely due to the rapid increase in the scale of data. The availability of large amounts of data is revolutionary for model training by the ...