2022
DOI: 10.1587/transinf.2021edp7184
|View full text |Cite
|
Sign up to set email alerts
|

SVM Based Intrusion Detection Method with Nonlinear Scaling and Feature Selection

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
3
1

Relationship

0
4

Authors

Journals

citations
Cited by 4 publications
(1 citation statement)
references
References 37 publications
0
1
0
Order By: Relevance
“…After the text has been vectorized, it is ready for computational processing by classification models. KNN [7], SVM [8], etc are not as effective in classifying large amounts of data. Deep learning models can solve this problem very well, such as recurrent neural networks(RNN) [9], LSTM [10], and convolutional neural networks(CNN), are commonly used for text classification.…”
Section: Classification Modelmentioning
confidence: 99%
“…After the text has been vectorized, it is ready for computational processing by classification models. KNN [7], SVM [8], etc are not as effective in classifying large amounts of data. Deep learning models can solve this problem very well, such as recurrent neural networks(RNN) [9], LSTM [10], and convolutional neural networks(CNN), are commonly used for text classification.…”
Section: Classification Modelmentioning
confidence: 99%