Feature selection is a process aimed at filtering out unrepresentative features from a given
dataset, usually allowing the later data mining and analysis steps to produce better results …

For a large number of network attacks, feature selection is used to improve intrusion
detection efficiency. A new mutual information algorithm of the redundant penalty between …

High-resolution range profile (HRRP) is increasingly employed in radar target recognition
under intricate ground scenarios. Such scenarios demand recognizing the specific type of a …

Unsupervised feature selection is a vital yet challenging topic for effective data learning.
Recently, 2-D feature selection methods show good performance on image analysis by …

Recently, the world has been dealing with a severe outbreak of COVID-19. The rapid
transmission of the virus causes mild to severe cases of cough, fever, body aches, organ …

Purpose Recent advancements in information technology and wearable devices have
revolutionized healthcare through health data analysis. Identifying significant relationships …

Feature selection is an important research issue in classification. As an effective global
optimization technique, Particle Swarm Optimization (PSO) algorithm has been widely …

In machine learning tasks, feature selection is an important data preprocessing step. It
improves the efficiency and prediction accuracy by removing redundant and irrelevant …

摘要分层分类是一种利用数据类别间层次结构关系进行分类的任务, 可以高效地组织和处理大
规模数据. 近些年来, 在这个受到越来越多关注的领域中涌现出许多重要的工作 …

Tumour detection medical applications utilize classification techniques to categorize
malicious and nonmalicious tumour features to provide an efficient medical diagnosis of the …