Papers by Mallinali Corona
The core of supervised classification consists in assigning to an object or phenomenon one of a p... more The core of supervised classification consists in assigning to an object or phenomenon one of a previously specified set of categories or classes. There are more complex problems where, instead of a single label, a set of labels are assigned to each instance, this is called multi-label classification. When the labels in a multi-label classification problem are ordered in a predefined structure, typically a tree or a Direct Acyclic Graph (DAG); the task is called Hierarchical Multi-label Classification (HMC). There are HMC methods that create a global model which take advantage of the relations (predefined structure) of the labels. However these methods tend to create too complex models unusable for large scale data. Other methods divide the problem in a set of subproblems, which usually does not benefit from the predefined structure. This thesis addresses the problem of hierarchical classification for tree and DAG structures considering large datasets with a considerable number of l...
In this paper we propose a novel hierarchical multi-label clas- sification approach for tree and ... more In this paper we propose a novel hierarchical multi-label clas- sification approach for tree and directed acyclic graph (DAG) hierarchies. The method predicts a single path (from the root to a leaf node) for tree hierarchies, and multiple paths for DAG hierarchies, by combining the predictions of every node in each possible path. In contrast with previous approaches, we evaluate all the paths, training local classifiers for each non-leaf node. The approach incorporates two contributions; (i) a cost is assigned to each node depending on the level it has in the hierarchy, giving more weight to correct predic- tions at the top levels; (ii) the relations between the nodes in the hierarchy are considered, by incorporating the parent label as in chained classifiers. The proposed approach was experimentally evaluated with 10 tree and 8 DAG hierarchi- cal datasets in the domain of protein function prediction. It was contrasted with various state-of-the-art hierarchical clas- sifiers using f...
Multi-label Classification for Tree and Directed Acyclic Graphs Hierarchies
Lecture Notes in Computer Science, 2014
Uploads
Papers by Mallinali Corona