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. 2015 Jun 1;6:24. doi: 10.1186/s13326-015-0019-z

Table 8.

Type-based learn to rank on training data

ID Sys P R F1 ID Sys P R F1
T019 SVMRank 0.46 0.15 0.23 T047 SVMRank 0.53 0.64 0.58
ListNet 0.47 0.13 0.20 ListNet 0.42 0.65 0.51
RankNet 0.47 0.11 0.18 RankNet 0.43 0.57 0.49
RankBoost 0.43 0.16 0.23 RankBoost 0.46 0.68 0.55
T020 SVMRank 0.32 0.57 0.41 T048 SVMRank 0.44 0.62 0.52
ListNet 0.29 0.50 0.36 ListNet 0.42 0.54 0.47
RankNet 0.33 0.42 0.37 RankNet 0.39 0.51 0.44
RankBoost 0.21 0.50 0.30 RankBoost 0.48 0.67 0.56
T033 SVMRank 0.01 0.32 0.02 T184 SVMRank 0.46 0.63 0.53
ListNet 0.01 0.48 0.02 ListNet 0.40 0.66 0.50
RankNet 0.01 0.48 0.03 RankNet 0.39 0.62 0.48
RankBoost 0.01 0.45 0.02 RankBoost 0.45 0.64 0.53
T037 SVMRank 0.34 0.33 0.33 T190 SVMRank 0.20 0.61 0.30
ListNet 0.26 0.24 0.25 ListNet 0.17 0.58 0.27
RankNet 0.22 0.21 0.22 RankNet 0.15 0.44 0.22
RankBoost 0.30 0.29 0.29 RankBoost 0.16 0.60 0.25
T046 SVMRank 0.29 0.66 0.40 T191 SVMRank 0.31 0.56 0.40
ListNet 0.25 0.67 0.36 ListNet 0.37 0.44 0.40
RankNet 0.27 0.61 0.37 RankNet 0.35 0.36 0.36
RankBoost 0.24 0.67 0.35 RankBoost 0.35 0.56 0.43

Note that the highest scoring system F1 for each semantic type is shown in bold.