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Table 8 F-Measure results when using each individual feature alone

From: A comparison and user-based evaluation of models of textual information structure in the context of cancer risk assessment

   a b c d e f g h i j k
S1 OBJ .39 .83 .71 .69 .52 .45 .45 .45 .54 .39 -
  METH - .47 .81 .74 .63 .49 - .46 .03 .42 .51
  RES - .76 .85 .86 .76 .70 .72 .69 .70 .68 .54
  CON - .72 .70 .65 .63 .53 .49 .57 .68 .20 -
S2 BKG .26 .73 .69 .67 .45 .38 .56 .33 .33 .29 -
  OBJ - .13 .72 .68 .54 .63 - .49 .48 .20 -
  METH - .50 .81 .72 .64 .47 - .47 .03 .42 .51
  RES - .76 .85 .87 .76 .72 .72 .70 .69 .68 .54
  CON - .70 .73 .71 .62 .51 .40 .61 .67 .23 -
  REL - - - - - - - - - - -
  FUT - - - - - - - - - - -
S3 HYP - - - - .67 - - - - - -
  MOT .18 .57 .70 .49 .39 .13 .36 .33 .30 .40 -
  BKG - - .54 .40 .21 - - .11 .06 .06 -
  GOAL - - .53 .33 .22 - .19 .31 - .25 -
  OBJT - - .73 .63 .60 .10 - .26 .32 - -
  EXP - .22 .63 .46 .33 .30 - .31 .07 .44 .25
  MOD - - - - - - - - - - -
  METH - - .82 .61 .39 .39 - .50 - .37 -
  OBS - .59 .75 .71 .63 .56 .56 .54 .48 .52 .47
  RES - - .87 .73 .41 .34 - .38 .24 .35 -
  CON - .74 .68 .65 .65 .50 .48 .49 .55 .21 -
  1. a-k: History, Location, Word, Bi-gram, Verb, Verb Class, POS, GR, Subj, Obj, Voice
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BMC Bioinformatics

ISSN: 1471-2105

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