research
∙
02/28/2023
Semi-Supervised Constrained Clustering: An In-Depth Overview, Ranked Taxonomy and Future Research Directions
Clustering is a well-known unsupervised machine learning approach capabl...
share
research
∙
02/25/2023
Semi-supervised Clustering with Two Types of Background Knowledge: Fusing Pairwise Constraints and Monotonicity Constraints
This study addresses the problem of performing clustering in the presenc...
research
∙
04/21/2022
Handling Imbalanced Classification Problems With Support Vector Machines via Evolutionary Bilevel Optimization
Support vector machines (SVMs) are popular learning algorithms to deal w...
research
∙
09/01/2021
An Empirical Study on the Joint Impact of Feature Selection and Data Resampling on Imbalance Classification
Real-world datasets often present different degrees of imbalanced (i.e.,...
research
∙
03/05/2020
Fuzzy k-Nearest Neighbors with monotonicity constraints: Moving towards the robustness of monotonic noise
This paper proposes a new model based on Fuzzy k-Nearest Neighbors for c...
research
∙
02/19/2020
Comprehensive Taxonomies of Nature- and Bio-inspired Optimization: Inspiration versus Algorithmic Behavior, Critical Analysis and Recommendations
In recent years, a great variety of nature- and bio-inspired algorithms ...
research
∙
02/19/2020
Taxonomy of bio-inspired algorithms
In recent years, a great variety of nature and bio-inspired algorithms h...
research
∙
01/16/2020
Smart Data based Ensemble for Imbalanced Big Data Classification
Big Data scenarios pose a new challenge to traditional data mining algor...
research
∙
10/22/2019
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI
In the last years, Artificial Intelligence (AI) has achieved a notable m...
research
∙
12/14/2018
A Tutorial on Distance Metric Learning: Mathematical Foundations, Algorithms and Software
This paper describes the discipline of distance metric learning, a branc...
research
∙
11/29/2018
A snapshot on nonstandard supervised learning problems: taxonomy, relationships and methods
Machine learning is a field which studies how machines can alter and ada...
research
∙
11/17/2018
Monotonic classification: an overview on algorithms, performance measures and data sets
Currently, knowledge discovery in databases is an essential step to iden...
research
∙
10/23/2018
OCAPIS: R package for Ordinal Classification And Preprocessing In Scala
Ordinal Data are those where a natural order exist between the labels. T...
research
∙
10/21/2018
Label Noise Filtering Techniques to Improve Monotonic Classification
The monotonic ordinal classification has increased the interest of resea...
research
∙
10/14/2018
DPASF: A Flink Library for Streaming Data preprocessing
Data preprocessing techniques are devoted to correct or alleviate errors...
research
∙
04/16/2018
BELIEF: A distance-based redundancy-proof feature selection method for Big Data
With the advent of Big Data era, data reduction methods are highly deman...
research
∙
01/04/2018
A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines
Many of the existing machine learning algorithms, both supervised and un...
research
∙
03/21/2017
