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Once the processed data is utilized in R, ARM is used to create association rules under various scenarios. A threshold value is established for both support and confidence, and these rules are generated accordingly. Following this, the rules are represented visually through a network graph.
Case 1: Considering Only two parameters and checking what correlates/ associates more with delay.
Case 1: Considering Only two parameters and checking what correlates/ associates more with delay.
The threshold support for this case was fixed as 0.05 (5%) and the threshold confidence was set as 0.05 (5%). Then the rules are arranged based on support, confidence, and lift and visualized using network graphs.
Top 15 rules based on Case1 sorted by decreasing order of support
Top 15 rules based on Case1 sorted by decreasing order of Confidence
Top 15 rules based on Case1 sorted by decreasing order of Lift
Network Graph based on Case1, rules arranged in decreasing order of lift
Analyzing the network graph and association rules for case 1 reveals significant insights. Notably, Southwest Airlines Co. stands out with the highest occurrence of weather delays, suggesting a correlation supported by a lift value exceeding 1. However, in instances of mild temperatures, despite relatively high support and confidence, the low lift indicates that it may not be a reliable rule to consider.
These observations are based on individual factors. Further analysis, incorporating additional variables and exploring their interactions, may unveil more substantial rules and patterns.
Case 2: Considering All the parameters and checking what correlates/ associates more with delay.
Case 2: Considering All the parameters and checking what correlates/ associates more with delay.
The threshold support for this case was fixed as .007 (0.7%) and the threshold confidence was set as 0.05 (5%). Then the rules are arranged based on support, confidence, and lift and visualized using network graphs.
Top 15 rules based on Case2 sorted by decreasing order of support
Top 15 rules based on Case2 sorted by decreasing order of Confidence
Top 15 rules based on Case2 sorted by decreasing order of Lift
Network Graph based on Case2, rules arranged in decreasing order of lift
Examining the network graph and association rules for case 2 provides more meaningful insights. Notably, Envoy Air originating from Illinois during cold temperatures is susceptible to weather delays, evidenced by a support value surpassing the threshold, a favorable confidence value, and a lift value greater than 1, indicating a reliable rule. Additionally, observations indicate that Spirit Airlines, commencing from Florida in warm temperatures, is also likely to experience weather delays, supported by a significant support value, a good confidence level, and a lift value exceeding 1. This information aids in understanding the correlation between airlines, their starting states, and weather conditions, contributing to the analysis of potential weather delays.
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