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NEW QUESTION: 1
On Cisco IOS Switches, which port security violation mode results in frames from non-allowed MAC address being dropped, log message created, and SNMP trap sent?
A. err-disabled
B. shutdown
C. protect
D. log
E. restrict
Answer: E
Explanation:
Explanation/Reference:
http://www.cisco.com/en/US/docs/switches/lan/catalyst6500/ios/12.2SX/configuration/guide/port_sec.pdf

NEW QUESTION: 2
Refer to the exhibit.

A VoWLAN has been deployed at a customer site, and users report that audio is choppy in some areas.
The exhibit captures a voice exchange between one phone that is associated to the AP at the end of the corridor (172.31.255.101) and another phone that is positioned in a conference room nearby. Which action enhances the voice application quality of experience?
A. Change the WLAN QoS profile to platinum.
B. Decrease the AP power level.
C. Disable higher data rates on the controller
D. Change the basic rate configuration on the WLC to include 54 Mbps.
Answer: D
Explanation:
Explanation/Reference:
Explanation:

NEW QUESTION: 3
Which of the following is the MAIN security concern for public cloud computing?
A. Unable to control physical access to the servers
B. Unable to run anti-virus scans
C. Unable to patch systems as needed
D. Unable to track log on activity
Answer: A

NEW QUESTION: 4
You have a dataset created for multiclass classification tasks that contains a normalized numerical feature set with 10,000 data points and 150 features.
You use 75 percent of the data points for training and 25 percent for testing. You are using the scikit-learn machine learning library in Python. You use X to denote the feature set and Y to denote class labels.
You create the following Python data frames:

You need to apply the Principal Component Analysis (PCA) method to reduce the dimensionality of the feature set to 10 features in both training and testing sets.
How should you complete the code segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:
Box 1: PCA(n_components = 10)
Need to reduce the dimensionality of the feature set to 10 features in both training and testing sets.
Example:
from sklearn.decomposition import PCA
pca = PCA(n_components=2) ;2 dimensions
principalComponents = pca.fit_transform(x)
Box 2: pca
fit_transform(X[, y])fits the model with X and apply the dimensionality reduction on X.
Box 3: transform(x_test)
transform(X) applies dimensionality reduction to X.
References:
https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html