All Outputs (4)

EPRENNID: An evolutionary prototype reduction based ensemble for nearest neighbor classification of imbalanced data (2016)
Journal Article

Classification problems with an imbalanced class distribution have received an increased amount of attention within the machine learning community over the last decade. They are encountered in a growing number of real-world situations and pose a chal... Read More about EPRENNID: An evolutionary prototype reduction based ensemble for nearest neighbor classification of imbalanced data.

kNN-IS: an iterative spark-based design of the k-nearest neighbors classifier for big data (2016)
Journal Article

The k-Nearest Neighbors classifier is a simple yet effective widely renowned method in data mining. The actual application of this model in the big data domain is not feasible due to time and memory restrictions. Several distributed alternatives base... Read More about kNN-IS: an iterative spark-based design of the k-nearest neighbors classifier for big data.

DPD-DFF: a dual phase distributed scheme with double fingerprint fusion for fast and accurate identification in large databases (2016)
Journal Article

Nowadays, many companies and institutions need fast and reliable identification systems that are able to deal with very large databases. Fingerprints are among the most used biometric traits for identification. In the current literature there are fin... Read More about DPD-DFF: a dual phase distributed scheme with double fingerprint fusion for fast and accurate identification in large databases.

Labelling strategies for hierarchical multi-label classification techniques (2016)
Journal Article

© 2016 Elsevier Ltd Many hierarchical multi-label classification systems predict a real valued score for every (instance, class) couple, with a higher score reflecting more confidence that the instance belongs to that class. These classifiers leave t... Read More about Labelling strategies for hierarchical multi-label classification techniques.