Feature Selection MethodsFeature Selection AlgorithmsFeature selection is an important topic in data mining, especially for high dimensional datasets. Feature selection (also known as subset selection) is a process commonly used in machine learning, wherein subsets of the features available from the ...
While we found a limited number of studies that utilized the model’s built-in feature importance list for feature selection in the context of the Credit Card Fraud Detection Dataset, we did not come across any studies that used SHAP for feature selection specifically in credit card fraud detect...
Performance Evaluation of Feature Selection Algorithms in Educational Data Mining Educational Data mining(EDM)is a prominent field concerned with developing methods for exploring the unique and increasingly large scale data that come fro... T Velmurugan,C Anuradha 被引量: 1发表: 2016年 Predicting Aca...
This study delves into a comparison between two feature selection methods: Shapley Additive exPlanation (SHAP)-value-based selection [3] and commonly used importance-based selection [4,5]. SHAP leverages game theory concepts to compute feature importance in two steps: training a classification model ...
We propose a method for the semi-automated refinement of the results of feature subset selection algorithms. Feature subset selection is a preliminary step... T May,A Bannach,J Davey,... - Visual Analytics Science & Technology 被引量: 67发表: 2011年 A Visualization and Design Tool (AVID) ...
Nature-inspired algorithms (NIA) are proven to be the potential tool for solving intricate optimization problems and aid in the development of better computational techniques. In recent years, these algorithms have raised considerable interest to optimize feature selection problems. In literature, NIA is...
The key idea in this method is to decompose an arbitrarily complex nonlinear problem into a set of locally linear ones through local information, and to learn globally feature relevance within the least squares loss framework. In contrast to other feature-selection algorithms for data regression, ...
With the proliferation of extremely high-dimensional data, feature selection algorithms have become indispensable components of the learning process. Strangely, despite extensive work on the stability of learning algorithms, the stability of feature selection algorithms has been relatively neglected. This stu...
Feature selection is the process of electing the most relevant features that contribute building a robust model (Liu & Motoda, 2012). Feature selection can be done manually or using several techniques and algorithms. It is an important step in building a robust Intrusion Detection System (IDS) ...
reduct, presenting a filter-wrapper method of selecting a bestε-approximate reduct, and examining the classification ability of the reduced system via a comparison with that of the reduced systems obtained by some reduction algorithms and some state-of-the-art feature selection methods. In ...