Question

In a machine learning-based IDS, feature selection is helpful to decrease the computational difficulty, eliminate data redundancy, enhance the detection rate of the machine learning techniques, simplify data, and reduce false alarms. True False

Name: in a machine learning based ids feature selection is helpful to decrease the computational difficulty eliminate data redundancy enhance the detection rate of the machine learning techniques 87116
Uploaded: 2022-06-01T20:27:18-08:00
Duration: 1 min 30 s
Channel: Tarandeep Singh
Description: in a machine learning based ids feature selection is helpful to decrease the computational difficulty eliminate data redundancy enhance the detection rate of the machine learning techniques 87116

          In a machine learning-based IDS, feature selection is helpful to decrease the computational difficulty, eliminate data redundancy, enhance the detection rate of the machine learning techniques, simplify data, and reduce false alarms.
True
False

Added by Emily U.

Computer Science and Information Technology

Trishna Knowledge Systems 2018 Edition

Instant Answer

Solved by Expert Tarandeep Singh

06/01/2022

Step 1

Feature selection is a process where you automatically select those features in your data that contribute most to the prediction variable or output in which you are interested. Show more…

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In a machine learning-based IDS, feature selection is helpful to decrease the computational difficulty, eliminate data redundancy, enhance the detection rate of the machine learning techniques, simplify data, and reduce false alarms. True False