Ensembles for feature selection: A review and future trends
V Bolón-Canedo, A Alonso-Betanzos - Information fusion, 2019 - Elsevier
Ensemble learning is a prolific field in Machine Learning since it is based on the assumption
that combining the output of multiple models is better than using a single model, and it …
that combining the output of multiple models is better than using a single model, and it …
Facial sentiment analysis using AI techniques: state-of-the-art, taxonomies, and challenges
With the advancements in machine and deep learning algorithms, the envision of various
critical real-life applications in computer vision becomes possible. One of the applications is …
critical real-life applications in computer vision becomes possible. One of the applications is …
An optimal pruning algorithm of classifier ensembles: dynamic programming approach
In recent years, classifier ensemble techniques have drawn the attention of many
researchers in the machine learning research community. The ultimate goal of these …
researchers in the machine learning research community. The ultimate goal of these …
An empirical comparison on state-of-the-art multi-class imbalance learning algorithms and a new diversified ensemble learning scheme
J Bi, C Zhang - Knowledge-Based Systems, 2018 - Elsevier
Class-imbalance learning is one of the most challenging problems in machine learning. As a
new and important direction in this field, multi-class imbalanced data classification has …
new and important direction in this field, multi-class imbalanced data classification has …
Preprocessed dynamic classifier ensemble selection for highly imbalanced drifted data streams
This work aims to connect two rarely combined research directions, ie, non-stationary data
stream classification and data analysis with skewed class distributions. We propose a novel …
stream classification and data analysis with skewed class distributions. We propose a novel …
Ensemble of deep neural networks with probability-based fusion for facial expression recognition
Convolutional neural network (CNN) is a very effective method to recognize facial emotions.
However, the preprocessing and selection of parameters of these methods heavily depend …
However, the preprocessing and selection of parameters of these methods heavily depend …
Optimized feature selection method using particle swarm intelligence with ensemble learning for cancer classification based on microarray datasets
Cancer is considered a leading cause of mortality in both developed and developing
countries. Cancer classification based on the microarray dataset has provided insight into …
countries. Cancer classification based on the microarray dataset has provided insight into …
A novel tree-based dynamic heterogeneous ensemble method for credit scoring
Y Xia, J Zhao, L He, Y Li, M Niu - Expert Systems with Applications, 2020 - Elsevier
Ensemble models have been extensively applied to credit scoring. However, advanced tree-
based classifiers have been seldom utilized as components of ensemble models. Moreover …
based classifiers have been seldom utilized as components of ensemble models. Moreover …
When does diversity help generalization in classification ensembles?
Ensembles, as a widely used and effective technique in the machine learning community,
succeed within a key element—“diversity.” The relationship between diversity and …
succeed within a key element—“diversity.” The relationship between diversity and …
Android based malware detection using a multifeature collaborative decision fusion approach
S Sheen, R Anitha, V Natarajan - Neurocomputing, 2015 - Elsevier
Smart mobile device usage has expanded at a very high rate all over the world. Since the
mobile devices nowadays are used for a wide variety of application areas like personal …
mobile devices nowadays are used for a wide variety of application areas like personal …