Feature selection and its use in big data: challenges, methods, and trends

M Rong, D Gong, X Gao - Ieee Access, 2019 - ieeexplore.ieee.org
Feature selection has been an important research area in data mining, which chooses a
subset of relevant features for use in the model building. This paper aims to provide an …

[HTML][HTML] A systematic review of social network sentiment analysis with comparative study of ensemble-based techniques

D Tiwari, B Nagpal, BS Bhati, A Mishra… - Artificial Intelligence …, 2023 - Springer
Sentiment Analysis (SA) of text reviews is an emerging concern in Natural Language
Processing (NLP). It is a broadly active method for analyzing and extracting opinions from …

[HTML][HTML] Bankruptcy prediction for SMEs using transactional data and two-stage multiobjective feature selection

G Kou, Y Xu, Y Peng, F Shen, Y Chen, K Chang… - Decision Support …, 2021 - Elsevier
Many bankruptcy prediction models for small and medium-sized enterprises (SMEs) are built
using accounting-based financial ratios. This study proposes a bankruptcy prediction model …

[HTML][HTML] Review of dimension reduction methods

S Nanga, AT Bawah, BA Acquaye, MI Billa… - Journal of Data Analysis …, 2021 - scirp.org
Purpose: This study sought to review the characteristics, strengths, weaknesses variants,
applications areas and data types applied on the various Dimension Reduction techniques …

A novel filter feature selection method for text classification: Extensive Feature Selector

B Parlak, AK Uysal - Journal of Information Science, 2023 - journals.sagepub.com
As the huge dimensionality of textual data restrains the classification accuracy, it is essential
to apply feature selection (FS) methods as dimension reduction step in text classification …

Wrapper and hybrid feature selection methods using metaheuristic algorithms for English text classification: A systematic review

OM Alyasiri, YN Cheah, AK Abasi, OM Al-Janabi - IEEE Access, 2022 - ieeexplore.ieee.org
Feature selection (FS) constitutes a series of processes used to decide which relevant
features/attributes to include and which irrelevant features to exclude for predictive …

A novel co-training-based approach for the classification of mental illnesses using social media posts

S Tariq, N Akhtar, H Afzal, S Khalid, MR Mufti… - Ieee …, 2019 - ieeexplore.ieee.org
Context: Recently, research community of certain domain showing their eagerness towards
the use of social media networks to gain constructive knowledge in decision making and …

Cyberbullying detection in social networks: A comparison between machine learning and transfer learning approaches

TH Teng, KD Varathan - IEEE Access, 2023 - ieeexplore.ieee.org
Information and Communication Technologies fueled social networking and facilitated
communication. However, cyberbullying on the platform had detrimental ramifications. The …

A study of the effects of stemming strategies on arabic document classification

YA Alhaj, J Xiang, D Zhao, MAA Al-Qaness… - IEEE …, 2019 - ieeexplore.ieee.org
Stemming is one of the most effective techniques, which has been adopted in many
applications, such as machine learning, machine translation, document classification (DC) …

A multi-objective feature selection method using Newton's law based PSO with GWO

P Dhal, C Azad - Applied Soft Computing, 2021 - Elsevier
In high dimensional data, the Feature Selection (FS) approach plays an important role in
overcoming accuracy, time complexity, and space complexity. This paper proposes a binary …