scholarly journals A Hybrid Filter/Wrapper Method for Feature Selection for Computer Worm Detection using Darknet Traffic

2018 ◽  
Vol 180 (44) ◽  
pp. 12-17 ◽  
Author(s):  
Ochieng Nelson ◽  
Waweru Mwangi ◽  
Ismail Ateya
Keyword(s):  
Feature Selection ◽  
Hybrid Filter ◽  
Worm Detection ◽  
Wrapper Method ◽  
Computer Worm ◽  
Selection For

Feature Selection For The Prediction Of Tropospheric Ozone Concentration Using A Wrapper Method

2011 ◽  
Vol 17 (4) ◽  
pp. 403-413 ◽  
Author(s):  
C. Okan Sakar ◽  
Goksel Demir ◽  
Olcay Kursun ◽  
Huseyin Ozdemir ◽  
Gokmen Altay ◽  
...  
Keyword(s):  
Feature Selection ◽  
Ozone Concentration ◽  
Tropospheric Ozone ◽  
Wrapper Method ◽  
Selection For

scholarly journals Effective Feature Selection for 5G IM Applications Traffic Classification

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Muhammad Shafiq ◽  
Xiangzhan Yu ◽  
Asif Ali Laghari ◽  
Dawei Wang
Keyword(s):  
Feature Selection ◽  
Classification Accuracy ◽  
Statistical Test ◽  
Traffic Classification ◽  
Features Selection ◽  
Traffic Flows ◽  
Selection Algorithm ◽  
Feature Selection Algorithm ◽  
Wrapper Method ◽  
Selection For

Recently, machine learning (ML) algorithms have widely been applied in Internet traffic classification. However, due to the inappropriate features selection, ML-based classifiers are prone to misclassify Internet flows as that traffic occupies majority of traffic flows. To address this problem, a novel feature selection metric named weighted mutual information (WMI) is proposed. We develop a hybrid feature selection algorithm named WMI_ACC, which filters most of the features with WMI metric. It further uses a wrapper method to select features for ML classifiers with accuracy (ACC) metric. We evaluate our approach using five ML classifiers on the two different network environment traces captured. Furthermore, we also apply Wilcoxon pairwise statistical test on the results of our proposed algorithm to find out the robust features from the selected set of features. Experimental results show that our algorithm gives promising results in terms of classification accuracy, recall, and precision. Our proposed algorithm can achieve 99% flow accuracy results, which is very promising.

scholarly journals An Iterative Hybrid Filter-Wrapper Approach to Feature Selection for Document Clustering

2009 ◽  
pp. 74-85 ◽  
Author(s):  
Mohammad-Amin Jashki ◽  
Majid Makki ◽  
Ebrahim Bagheri ◽  
Ali A. Ghorbani
Keyword(s):  
Feature Selection ◽  
Document Clustering ◽  
Hybrid Filter ◽  
Wrapper Approach ◽  
Selection For

A two-stage feature selection and intelligent fault diagnosis method for rotating machinery using hybrid filter and wrapper method

2018 ◽  
Vol 275 ◽  
pp. 2426-2439 ◽  
Author(s):  
Xiaolong Zhang ◽  
Qing Zhang ◽  
Miao Chen ◽  
Yuantao Sun ◽  
Xianrong Qin ◽  
...  
Keyword(s):  
Feature Selection ◽  
Fault Diagnosis ◽  
Rotating Machinery ◽  
Intelligent Fault Diagnosis ◽  
Hybrid Filter ◽  
Two Stage ◽  
Wrapper Method ◽  
Diagnosis Method

A novel hybrid filter/wrapper method for feature selection in archaeological ceramics classification by laser-induced breakdown spectroscopy

The Analyst ◽  
2021 ◽  
Author(s):  
Fangqi Ruan ◽  
Lin Hou ◽  
Tianlong Zhang ◽  
Hua Li
Keyword(s):  
Feature Selection ◽  
Cultural Heritage ◽  
Analytical Tool ◽  
Laser Induced Breakdown Spectroscopy ◽  
Chemometric Methods ◽  
Hybrid Filter ◽  
Archaeological Ceramics ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown ◽  
Wrapper Method

Laser-induced breakdown spectroscopy (LIBS) has been appreciated as a valuable analytical tool in the cultural heritage field owing to its unique technological superiority, particularly in combination with chemometric methods.

Hybrid filter–wrapper feature selection for short-term load forecasting

2015 ◽  
Vol 40 ◽  
pp. 17-27 ◽  
Author(s):  
Zhongyi Hu ◽  
Yukun Bao ◽  
Tao Xiong ◽  
Raymond Chiong
Keyword(s):  
Feature Selection ◽  
Load Forecasting ◽  
Hybrid Filter ◽  
Short Term ◽  
Short Term Load Forecasting ◽  
Selection For ◽  
Wrapper Feature Selection

FEATURE SELECTION FOR THE DETECTION OF EPILEPSY BY USING EEG PHYSIOLOGICAL SIGNAL

2017 ◽  
Vol 4 (2) ◽  
pp. 17
Author(s):  
CHANDANI MANISHA ◽  
KUMAR ARUN ◽  
◽  
Keyword(s):  
Feature Selection ◽  
Physiological Signal ◽  
Selection For

Chicken Algorithm Based Feature Selection For Arabic Information Searching System

2019 ◽  
pp. 389
Author(s):  
زينب عبدالأمير ◽  
علياء كريم عبدالحسن
Keyword(s):  
Feature Selection ◽  
Information Searching ◽  
Selection For
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