Adherence predictor variables in AIDS patients: an empirical study using the data mining-based RFM model

Table 6 C5.0 algorithm analysis results

Item	Data binning	Node/model¹	Predictor variable importance	Prediction model accuracy (%)			Amount of data (sets) indicating good/poor adherence
Training set	90% data	R ≤ 3/[Model: 1] R > 3/[Model: 2]	R = 1	Correct	9582	100%	Good adherence	8846	0
				Wrong	0	0	Poor adherence	0	736
				Total	9582	–	Total	9582
Test set	10% data	R ≤ 3/[Model: 1] R > 3/[Model: 2]	R = 1	Correct	1032	100%	Good adherence	957	0
				Wrong	0	0	Poor adherence	0	75
				Total	1032	–	Total	1074

90% of the data was used as the training set to construct the adherence prediction model, and the remaining 10% was used as the test set to validate the model
¹Nodes: Recency: R; 3 months was used as a node to divide R into two categories: for Model 1, R ≤ 3 months; indicating good adherence; for Model 2, R > 3 months, indicating that poor adherence

ISSN: 1742-6405