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NEW QUESTION: 1
A commercial airline uses its database to develop the following regression model to predict the cost of a flight Y (in dollars) by number of passengers:
Y = 1,570 +40 7x
Which of the following statements is correct in relation to the airline'?
A. The cost of a flight will increase by $40.7 when an additional passenger is added to the flight.
B. The positive intercept in the model indicates a positive relationship between the cost of a flight and the number of passengers.
C. The regression model makes accurate predictions for this commercial airline, therefore it will provide good forecasts for other commercial airlines.
D. If each pair of data points is plotted on a graph with Y on the vertical axis and X on the horizontal axis, there will be a downward sloping line.
Answer: D

NEW QUESTION: 2
Ein Unternehmen genehmigt ein neues Projekt zur Erweiterung seines Produktportfolios. Der Sponsor erklärt dem Projektmanager die Bedeutung dieses Projekts und sagt, dass es beim ersten Versuch erfolgreich sein muss. Es ist eine neue Domäne für das Unternehmen, und sie müssen mehr internes Wissen über das neue Produkt entwickeln.
Welche Risikostrategie sollte angewendet werden, da sich das Unternehmen Fehler nicht leisten kann?
A. Übertragen
B. Akzeptieren
C. Mildern
D. SIAvoid
Answer: D

NEW QUESTION: 3
You need to configure the Permutation Feature Importance module for the model training requirements.
What should you do? To answer, select the appropriate options in the dialog box in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:
Box 1: 500
For Random seed, type a value to use as seed for randomization. If you specify 0 (the default), a number is generated based on the system clock.
A seed value is optional, but you should provide a value if you want reproducibility across runs of the same experiment.
Here we must replicate the findings.
Box 2: Mean Absolute Error
Scenario: Given a trained model and a test dataset, you must compute the Permutation Feature Importance scores of feature variables. You need to set up the Permutation Feature Importance module to select the correct metric to investigate the model's accuracy and replicate the findings.
Regression. Choose one of the following: Precision, Recall, Mean Absolute Error , Root Mean Squared Error, Relative Absolute Error, Relative Squared Error, Coefficient of Determination References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/permutation-feature-importance

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