In multi-label learning, each training example is associated with a set of labels and the task is to predict the proper label set for the unseen example. Due to the tremendous (ex...
When different subsamples of the same data set are used to induce classification trees, the structure of the built classifiers is very different. The stability of the structure of ...
A boosting algorithm based on cellular genetic programming to build an ensemble of predictors is proposed. The method evolves a population of trees for a fixed number of rounds an...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
The quest to nd models usefully characterizing data is a process central to the scienti c method, and has been carried out on many fronts. Researchers from an expanding number of ...
Accurate and less invasive personalized predictive medicine can spare many breast cancer patients from receiving complex surgical biopsies, unnecessary adjuvant treatments and its...
Umer Khan, Hyunjung Shin, Jongpill Choi, Minkoo Ki...