An Interpretable Classification Framework for Information Extraction from Online Healthcare Forums

Table 5

Top 10 feature contributions for medication and symptom class in a random forest model.

Feature	Back.	Med.	Sym.
Top 10 FC for medication sentences
Prescribed = 1	−0.00275	0.01195	−0.00920
(PRP, CD, CD) = 1	−0.00251	0.01156	−0.00905
Morpho. = 1	−0.00206	0.00660	−0.00455
hlca = 1	−0.00071	0.00559	−0.00489
(NN, SYMP, SYMP, CC) = 0	0.00115	0.00429	−0.00544
sosy = 0	0.00191	0.00406	−0.00597
(PRP, CD, IN, NN, NN) = 1	−0.00075	0.00402	−0.00327
(CD, IN, CD, CD) = 1	−0.00120	0.00396	−0.00276
thr. Crt. = 0	0.00154	0.00381	−0.00535
(PRP, CD, JJ, JJ) = 1	−0.00086	0.00362	−0.00276
Top 10 FC for symptom sentences
sosy = 1	−0.00589	−0.00783	0.01371
Prescribed = 0	0.00234	−0.015734	0.01339
thr. Crt. = 1	−0.00381	−0.00683	0.01064
(PRP, CD, CD) = 0	0.00271	−0.01264	0.00993
(SYMP, SYMP, SYMP) = 1	−0.00330	−0.00564	0.00895
(NN, SYMP, SYMP, CC) = 1	−0.00209	−0.00667	0.00876
Position < vth1	−0.00334	−0.00540	0.00874
patf = 1	−0.00254	−0.00379	0.00633
(SYMP, CC, JJ) = 1	−0.00172	−0.00404	0.00576
Word count > vth2	−0.00131	−0.00423	0.00554