12 Questions
What is a key aspect to consider when applying clustering techniques in the context of airline route choice?
Defining a metric of similarity between data
In the study by Evans and Lee, what method was used to identify route candidates?
Hierarchical clustering on historical data
What are the potential problems if a wrong metric for clustering is chosen in the context of airline route choice?
The operation produces results that have no meaning
What technique was proposed to forecast airline route choice through a combination of machine learning and visual analytics?
Clustering methods followed by visual analytics and multinomial logistic regression
What percentage of flights between OD pairs closer than 1000 km are mostly served by one airline?
About 58%
How many trajectory clusters are typically being used at distances closer than 1000 km?
One
What is the reason for the predominant use of one trajectory cluster even when more than one cluster can be identified?
To minimize operational costs
How might the inclusion of environmental indicators affect airline routing decisions?
Bring a change in the choice of aircraft types and trajectories
What is the main purpose of the study described in the text?
Examine usual choices airlines make in routing and their relation with aircraft types and flight costs
What percentage of city pairs show a clear relation between trajectory clusters and airlines?
49%
What type of flights make up about half of all flights described in the text?
Flights less than 1000 km long
What statistical test is used to evaluate the relations between variables in the study?
Chi-squared test
Explore the application of machine learning and visual analytics in forecasting airline route choice, focusing on data from Istanbul to Paris airports. Learn about clustering methods, visual analytics, and multinomial logistic regression models for predicting route choices.
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