[HTML][HTML] Weighted Ensemble with one-class Classification and Over-sampling and Instance selection (WECOI): An approach for learning from imbalanced data …

I Czarnowski - Journal of Computational Science, 2022 - Elsevier
Learning from imbalanced data streams is one of the challenges associated with
classification algorithms and learning classifiers. The goal of this paper is to propose and …

Organizational Data Classification Based on the Importance Concept of Complex Networks

MG Carneiro, L Zhao - IEEE transactions on neural networks …, 2017 - ieeexplore.ieee.org
Data classification is a common task, which can be performed by both computers and
human beings. However, a fundamental difference between them can be observed …

Adaptive graph construction using data self-representativeness for pattern classification

F Dornaika, A Bosaghzadeh - Information Sciences, 2015 - Elsevier
Graph construction from data constitutes a pre-stage in many machine learning and
computer vision tasks, like semi-supervised learning, manifold learning, and spectral …

Musical rhythmic pattern extraction using relevance of communities in networks

AE Coca, L Zhao - Information Sciences, 2016 - Elsevier
The rhythmic background of a musical piece is usually composed of featured elements that
define the musical genre. For each song, such elements form rhythmic patterns, the most …

Ensemble classifier for mining data streams

I Czarnowski, P Jędrzejowicz - Procedia Computer Science, 2014 - Elsevier
The problem addressed in this paper concerns mining data streams with concept drift. The
goal of the paper is to propose and validate a new approach to mining data streams with …

Ensemble online classifier based on the one-class base classifiers for mining data streams

I Czarnowski, P Jędrzejowicz - Cybernetics and Systems, 2015 - Taylor & Francis
The problem addressed in this study concerns mining data streams with concept drift. The
goal of the article is to propose and validate a new approach to mining data streams with …

Attribute-based decision graphs: a framework for multiclass data classification

JRB Junior, M do Carmo Nicoletti, L Zhao - Neural Networks, 2017 - Elsevier
Graph-based algorithms have been successfully applied in machine learning and data
mining tasks. A simple but, widely used, approach to build graphs from vector-based data is …

Learning from imbalanced data streams based on over-sampling and instance selection

I Czarnowski - International conference on computational science, 2021 - Springer
Learning from imbalanced data streams is one of the challenges for classification algorithms
and learning classifiers. The goal of the paper is to propose and validate a new approach for …

Feature Ranking from Random Forest Through Complex Network's Centrality Measures: A Robust Ranking Method Without Using Out-of-Bag Examples

AH Cantão, AA Macedo, L Zhao… - European Conference on …, 2022 - Springer
The volume of available data in recent years has rapidly increased. In consequence,
datasets commonly end up with many irrelevant features. That increase may disturb human …

Using the k-associated optimal graph to provide counterfactual explanations

AT da Silva, JR Bertini - 2022 IEEE International Conference on …, 2022 - ieeexplore.ieee.org
Only recently have data mining results been thought to aid human interpretability.
Explanations are useful to understand the reasons why (or why not) the model has (or …