26 citations · 49 across the 4 of their papers we have counts for
3 papers · 1 filter
Reducing Data Complexity using Autoencoders with Class-informed Loss Functions
David Charte, Francisco Charte, Francisco Herrera
Available data in machine learning applications is becoming increasingly complex, due to higher dimensionality and difficult classes. There exists a wide variety of approaches to m…
Revisiting Data Complexity Metrics Based on Morphology for Overlap and Imbalance: Snapshot, New Overlap Number of Balls Metrics and Singular Problems Prospect
José Daniel Pascual-Triana, David Charte, Marta Andrés Arroyo +2
Data Science and Machine Learning have become fundamental assets for companies and research institutions alike. As one of its fields, supervised classification allows for class pre…
Smart Data driven Decision Trees Ensemble Methodology for Imbalanced Big Data
Diego García-Gil, Salvador García, Ning Xiong +1
Differences in data size per class, also known as imbalanced data distribution, have become a common problem affecting data quality. Big Data scenarios pose a new challenge to trad…