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Efficient Multiclass Classification Using Feature Selection in High ...


Efficient Multiclass Classification Using Feature Selection in High ...

This paper proposes a novel feature-selection approach that combines filter and wrapper techniques to select optimal features using Mutual Information.

(PDF) Efficient Multiclass Classification Using Feature Selection in ...

Results show that the proposed algorithm can reduce features by more than 75% in datasets with large features and achieve a maximum accuracy of ...

Efficient Multiclass Classification Using Feature Selection in High ...

This paper proposes a novel feature-selection approach that combines filter and wrapper techniques to select optimal features using Mutual Information with ...

Efficient Multiclass Classification Using Feature Selection in High ...

Efficient Multiclass Classification Using Feature Selection in High-Dimensional Datasets. Language: English; Authors: Kumar, Ankur1 (AUTHOR) saxenaanksrms ...

Efficient Multiclass Classification Using Feature Selection in High ...

Efficient Multiclass Classification Using Feature Selection in. High-Dimensional Datasets. Ankur Kumar 1, Avinash Kaur 2,*, Parminder Singh 1 ...

Paper | Scholar-Chat

Efficient Multiclass Classification Using Feature Selection in High-Dimensional Datasets. Ankur Kumar, Avinash Kaur, Parminder Singh, ..., W. Boulila - null.

Efficient feature selection and multiclass classification with ... - PubMed

Multiclass classification and feature (variable) selections are commonly encountered in many biological and medical applications.

Efficient feature selection and multiclass classification with ...

Their performance is degraded when applied to high dimensional data. On the other hand, model-based methods such as logistic regression require the ...

Efficient Feature Selection and Multiclass Classification with ...

Their performance is degraded when applied to high dimensional data. On the other hand, model-based methods such as logistic regression require ...

Efficient feature selection and multiclass classification with ...

the rest scheme even if the original multiclass problem is balanced. By combining instance-based and model-based learning, we propose an efficient learning ...

Feature Selection for Multiclass Problems Based on Information ...

Before a pattern classifier can be properly designed, it is necessary to consider the feature extraction and data reduction problems.

Effective Feature Selection for Multi-class Classification Models

The enhancement of features' discrimination power using fuzzy clustering analyses is proposed in this paper. In addition, a set of low-dependent features ...

Multiclass feature selection with metaheuristic optimization algorithms

Usually, the wrapper approach includes the classification algorithm, and it interacts with the classifier. Although this method usually presents ...

GB-AFS: graph-based automatic feature selection for multi-class ...

This paper introduces a novel graph-based filter method for automatic feature selection (abbreviated as GB-AFS) for multi-class classification tasks.

MEL: Efficient Multi-Task Evolutionary Learning for High ... - arXiv

Zhou, “An evolutionary multitasking- based feature selection method for high-dimensional classification,” IEEE. Trans. Cybern., vol. 52, no ...

What feature selection method is best for a multi class classification ...

When training several different machine learning models without any feature selection and all 128 features, I get some good results mainly with ...

Electronics | Free Full-Text | Efficient Multiclass Classification Using ...

Efficient Multiclass Classification Using Feature Selection in High-Dimensional Datasets. Electronics 2023, 12, 2290. https://doi.org/10.3390 ...

Efficient Feature Selection and Multiclass Classification with ...

Their performance is degraded when applied to high dimensional data. On the other hand, model-based methods such as logistic regression require the ...

Effective Feature Selection Strategy for Supervised Classification ...

Additionally, k-Nearest Neighbor ( k -NN) and Support Vector Machine (SVM) are quality estimators. On 18 multi-scale benchmarks, the IBAO algorithm is compared ...

Feature Selection for Classification: A Review

Developing algorithms of feature selection for classification with high classification ... Multi-task feature learning via efficient l 2, 1-norm minimization. In ...