This paper presents an approach to the problem of binary classification using ensemble neural networks based on interval neutrosophic sets and bagging technique. Each component in the ensemble consists of a pair of neural networks trained to predict the degree of truth and false membership values
This chapter presents the state of the art in classifier ensembles and their comparative performance...
This paper proposes a classification method for environmental sounds based on neural networks. Howev...
Abstract. In this paper we present a new method to create neural network ensembles. In an ensemble m...
This paper presents an approach to the problem of binary classification using ensemble neural networ...
This paper presents an ensemble neural network and interval neutrosophic sets approach to the proble...
Artificial neural networks(ANNs) are computing models for information processing and pattern identif...
This paper presents an innovative approach to solve the problem of multiclass classification. One-ag...
This paper describes the integration of neural network ensembles and interval neutrosophic sets usin...
This paper presents a new approach to the problem of multiclass classification. The proposed approac...
In this paper, the classification results obtained from several kinds of support vector machines (SV...
The ensemble of evolving neural networks, which employs neural networks and genetic algorithms, is d...
This paper describes the integration of neural network ensembles and interval neutrosophic sets usin...
Abstract — In this study we introduce a neural network ensemble composed of several linear perceptro...
Ensemble approaches have been shown to enhance classification by combining the outputs from a set of...
Abstract. In this work we propose a new method to create neural net-work ensembles. Our methodology ...
This chapter presents the state of the art in classifier ensembles and their comparative performance...
This paper proposes a classification method for environmental sounds based on neural networks. Howev...
Abstract. In this paper we present a new method to create neural network ensembles. In an ensemble m...
This paper presents an approach to the problem of binary classification using ensemble neural networ...
This paper presents an ensemble neural network and interval neutrosophic sets approach to the proble...
Artificial neural networks(ANNs) are computing models for information processing and pattern identif...
This paper presents an innovative approach to solve the problem of multiclass classification. One-ag...
This paper describes the integration of neural network ensembles and interval neutrosophic sets usin...
This paper presents a new approach to the problem of multiclass classification. The proposed approac...
In this paper, the classification results obtained from several kinds of support vector machines (SV...
The ensemble of evolving neural networks, which employs neural networks and genetic algorithms, is d...
This paper describes the integration of neural network ensembles and interval neutrosophic sets usin...
Abstract — In this study we introduce a neural network ensemble composed of several linear perceptro...
Ensemble approaches have been shown to enhance classification by combining the outputs from a set of...
Abstract. In this work we propose a new method to create neural net-work ensembles. Our methodology ...
This chapter presents the state of the art in classifier ensembles and their comparative performance...
This paper proposes a classification method for environmental sounds based on neural networks. Howev...
Abstract. In this paper we present a new method to create neural network ensembles. In an ensemble m...
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