Clustering is a well-known unsupervised machine learning approach capabl...
This study addresses the problem of performing clustering in the presenc...
Support vector machines (SVMs) are popular learning algorithms to deal w...
Real-world datasets often present different degrees of imbalanced (i.e.,...
This paper proposes a new model based on Fuzzy k-Nearest Neighbors for
c...
In recent years, a great variety of nature- and bio-inspired algorithms ...
In recent years, a great variety of nature and bio-inspired algorithms h...
Big Data scenarios pose a new challenge to traditional data mining
algor...
In the last years, Artificial Intelligence (AI) has achieved a notable
m...
This paper describes the discipline of distance metric learning, a branc...
Machine learning is a field which studies how machines can alter and ada...
Currently, knowledge discovery in databases is an essential step to iden...
Ordinal Data are those where a natural order exist between the labels. T...
The monotonic ordinal classification has increased the interest of
resea...
Data preprocessing techniques are devoted to correct or alleviate errors...
With the advent of Big Data era, data reduction methods are highly deman...
Many of the existing machine learning algorithms, both supervised and
un...
Fingerprint classification is one of the most common approaches to accel...