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NEW QUESTION: 1
A. Option D
B. Option B
C. Option A
D. Option C
Answer: C
NEW QUESTION: 2
A network administrator is troubleshooting an EIGRP connection between RouterA, IP address 10.1.2.1, and RouterB, IP address 10.1.2.2. Given the debug output on RouterA, which two statements are true? (Choose two.)
A. RouterA will not form an adjacency with RouterB.
B. RouterA will form an adjacency with RouterB.
C. RouterA received a hello packet with mismatched metric-calculation mechanisms.
D. RouterA received a hello packet with mismatched hello timers.
E. RouterA received a hello packet with mismatched autonomous system numbers.
F. RouterA received a hello packet with mismatched authentication parameters.
Answer: A,C
NEW QUESTION: 3
DRAG DROP
Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
A travel agency named Margie's Travel sells airline tickets to customers in the United States.
Margie's Travel wants you to provide insights and predictions on flight delays. The agency is considering implementing a system that will communicate to its customers as the flight departure nears about possible delays due to weather conditions. The flight data contains the following attributes:
The weather data contains the following attributes: AirportID, ReadingDate (YYYY/MM/DD HH), SkyConditionVisibility, WeatherType, WindSpeed, StationPressure, PressureChange, and HourlyPrecip.
You need to remove the bias and to identify the columns in the input dataset that have the greatest predictive power.
Which module should you use for each requirement? To answer, drag the appropriate modules to the correct requirements. Each module may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
References:
https://gallery.cortanaintelligence.com/Experiment/Binary-Classification-Flight-delay- prediction-3
https://msdn.microsoft.com/library/azure/038d91b6-c2f2-42a1-9215-1f2c20ed1b40