One of the main reasons is that many loss functions are too sensitive to sample points far from their classes. In this paper, ...

In supervised learning, a set of input variables, such as blood metabolite or gene expression levels, are used to predict a quantitative response variable like hormone level or a qualitative one ...

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

Decision Trees are a popular machine learning method that partitions the feature space into smaller regions and models the response variable in each region using simple rules. However, Decision Trees ...

Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization by rapidly predicting molecular interactions and properties. For instance, ...