Stability assessment of feature selection algorithms on homogeneous datasets: A study for sensor array optimization problem
A feature selection algorithm (FSA) is used to eliminate redundant and irrelevant features.
Obviously, it can reduce dimensionality as well as the complexity of the original problem …
Obviously, it can reduce dimensionality as well as the complexity of the original problem …
A joint feature selection framework for multivariate resource usage prediction in cloud servers using stability and prediction performance
Resource provisioning in cloud servers depends on future resource utilization of different
jobs. As resource utilization trends vary dynamically, effective resource provisioning requires …
jobs. As resource utilization trends vary dynamically, effective resource provisioning requires …
A feature selection approach based on a similarity measure for software defect prediction
Q Yu, S Jiang, R Wang, H Wang - Frontiers of Information Technology & …, 2017 - Springer
Software defect prediction is aimed to find potential defects based on historical data and
software features. Software features can reflect the characteristics of software modules …
software features. Software features can reflect the characteristics of software modules …
Feature selection for high-dimensional data: the issue of stability
B Pes - 2017 IEEE 26th International Conference on Enabling …, 2017 - ieeexplore.ieee.org
Feature selection has become a necessary step to the analysis of high-dimensional datasets
coming from several application domains (eg, web data, document and image analysis …
coming from several application domains (eg, web data, document and image analysis …
An Evaluation of Feature Selection Robustness on Class Noisy Data
S Pau, A Perniciano, B Pes, D Rubattu - Information, 2023 - mdpi.com
With the increasing growth of data dimensionality, feature selection has become a crucial
step in a variety of machine learning and data mining applications. In fact, it allows …
step in a variety of machine learning and data mining applications. In fact, it allows …
Evaluating feature selection robustness on high-dimensional data
B Pes - Hybrid Artificial Intelligent Systems: 13th International …, 2018 - Springer
With the explosive growth of high-dimensional data, feature selection has become a crucial
step of machine learning tasks. Though most of the available works focus on devising …
step of machine learning tasks. Though most of the available works focus on devising …
Evolutionary Algorithms' Feature Selection Stability Improvement System
Y Liu, X Diao, J Cao, L Zhang - … Conference, BIC-TA 2017, Harbin, China …, 2017 - Springer
In order to improve the feature selection stability based on evolutionary algorithms, an
evolutionary algorithms' feature selection stability improvement system is proposed. Three …
evolutionary algorithms' feature selection stability improvement system is proposed. Three …
一种面向软件缺陷预测的相似性度量特征选择方法
Q Yu, S Jiang, R Wang, H Wang, AQ Yu, AS Jiang… - Frontiers, 2017 - jzus.zju.edu.cn
软件缺陷预测旨在通过历史数据和能反映软件模块特性的软件特征来发现潜在缺陷. 然而,
有的特征可能与类别(有缺陷或无缺陷) 的相关性较高, 有的特征可能是冗余的或无关的 …
有的特征可能与类别(有缺陷或无缺陷) 的相关性较高, 有的特征可能是冗余的或无关的 …
Optimal design of wide area based on fuzzy controller and intelligent method
S Setayeshi, VB Rad, A Noruzi… - International Journal of …, 2017 - World Scientific
Recently, the controller using wide-area measurement systems (WAMS) signals has been
proposed by researchers. But, an unavoidable delay before the wide-area signals exists …
proposed by researchers. But, an unavoidable delay before the wide-area signals exists …