10 citations · 10 across the 4 of their papers we have counts for
4 papers
Semi-Supervised Constrained Clustering: An In-Depth Overview, Ranked Taxonomy and Future Research Directions
Germán González-Almagro, Daniel Peralta, Eli De Poorter +2
Clustering is a well-known unsupervised machine learning approach capable of automatically grouping discrete sets of instances with similar characteristics. Constrained clustering…
Semi-supervised Clustering with Two Types of Background Knowledge: Fusing Pairwise Constraints and Monotonicity Constraints
Germán González-Almagro, Juan Luis Suárez, Pablo Sánchez-Bermejo +2
This study addresses the problem of performing clustering in the presence of two types of background knowledge: pairwise constraints and monotonicity constraints. To achieve this,…
Monotonic classification: an overview on algorithms, performance measures and data sets
José-Ramón Cano, Pedro Antonio Gutiérrez, Bartosz Krawczyk +2
Currently, knowledge discovery in databases is an essential step to identify valid, novel and useful patterns for decision making. There are many real-world scenarios, such as bank…
Label Noise Filtering Techniques to Improve Monotonic Classification
José-Ramón Cano, Julián Luengo, Salvador García
The monotonic ordinal classification has increased the interest of researchers and practitioners within machine learning community in the last years. In real applications, the prob…