A classification framework for exploiting sparse multi-variate temporal features with application to adverse drug event detection in medical records

Table 3 Comparison between lr and plain (first row) and between lr and sl (second row), for different values of the sparsity threshold

	0.2	0.3	0.5	0.7	0.9	0.95	1.0	Overall
lr vs plain	lr (10)	plain (8)	plain (8)	lr (11)*	lr(11)	lr(9)	lr(10)*	lr (9)
lr vs sl	lr (13)*	lr (14)*	lr (13)*	lr (10)*	lr (13)*	lr (10)	lr(9)	lr (12)*

Each cell of the table reports the method achieving the highest number of best performances (in brackets) among all of the ADE datasets for a particular sparsity level. The last column refers to the number of best AUCs obtained on the ADE datasets regardless of τ_sp. An asterisk marks those cases which are proved to be statistically significant within a confidence interval of 0.05

ISSN: 1472-6947