Table 4 Relevant rules illustrating the association between different categories of words
From: A machine learning approach to analyze customer satisfaction from airline tweets
Rule no. | Association rule | Support | Confidence | Lift |
|---|---|---|---|---|
R1 | [CCB = 0 AND FQL = 0] → [Sentiment = 0] | 0.3 | 0.86 | 1.34 |
R2 | [FQL = 0] → [CCB = 0] | 0.4 | 0.91 | 1.63 |
R3 | [FQL = 1] → [CCB = 1] | 0.4 | 0.93 | 1.69 |
R4 | [FQL = 1 AND CCB = 1] → [Sentiment = 1] | 0.3 | 0.86 | 1.35 |
R5 | [FDC = 1] → [LOB = 1] | 0.3 | 0.64 | 1.02 |
R6 | [FDC = 0 AND CCB = 0] → [IFC = 0] | 0.3 | 0.87 | 1.65 |
R7 | [IFC = 0] → [Sentiment = 0] | 0.5 | 0.92 | 2.35 |
R8 | [CCB = 0] → [Sentiment = 0] | 0.5 | 0.85 | 1.48 |
R9 | [LOB = 1] → [Sentiment = 0] | 0.2 | 0.69 | 1.06 |
R10 | [FQL = 1] → [Sentiment = 1] | 0.2 | 0.61 | 0.92 |