Supplementary Material: HAUS-rules
This website contains supplementary material to the paper ESWA-D-21-00806 submitted to be taken into account for possible publication in Expert Systems With Applications.
Summary:
- Results obtained by the analyzed algorithms on each of the datasets
- Dataset for the biological problem
Results obtained by the analyzed algorithms on each of the datasets
Synthetic 1
Algorithm | #R | Av_Amp (s) | Av_Sup (s) | Av_Conf (s) | Av_Lift (s) | Av_CF (s) | Av_YulesQ (s) | aveUti (s) | CF*aveUti (s) |
---|---|---|---|---|---|---|---|---|---|
CMRules | 343 | 3.31 (0.88) | 0.58 (0.07) | 0.85 (0.07) | 0.97 (0.04) | -0.04 (0.06) | -0.92 (3.86) | 9324.64 (2880.88) | -372.99 (509.62) |
HUSRM | 1566 | 10.89 (0.34) | 0.01 (0.01) | 0.84 (0.1) | 2.71 (0.32) | 0.76 (0.14) | 0.84 (0.11) | 129.6 (18.08) | 98.3 (23.59) |
HAUS-rules | 17 | 3.53 (1.1) | 0.31 (0.18) | 0.95 (0.07) | 1.09 (0.12) | 0.74 (0.24) | 0.86 (0.21) | 5650.87 (3949.28) | 4181.64 (614.85) |
Synthetic 2
Algorithm | #R | Av_Amp (s) | Av_Sup (s) | Av_Conf (s) | Av_Lift (s) | Av_CF (s) | Av_YulesQ (s) | aveUti (s) | CF*aveUti (s) |
---|---|---|---|---|---|---|---|---|---|
CMRules | 322 | 3.26 (0.84) | 0.58 (0.07) | 0.84 (0.07) | 0.96 (0.04) | -0.04 (0.06) | -0.77 (1.34) | 18554.7 (5800.96) | -742.2 (1024.53) |
HUSRM | 884 | 10.85 (0.39) | 0.02 (0.01) | 0.76 (0.06) | 1.67 (0.17) | 0.55 (0.13) | 0.58 (0.13) | 493.58 (38.56) | 271.47 (63.03) |
HAUS-rules | 11 | 3.28 (1.14) | 0.31 (0.21) | 0.92 (0.1) | 1.15 (0.18) | 0.59 (0.29) | 0.63 (0.25) | 11526.16 (9086.71) | 6800.43 (1943.6) |
Synthetic 3
Algorithm | #R | Av_Amp (s) | Av_Sup (s) | Av_Conf (s) | Av_Lift (s) | Av_CF (s) | Av_YulesQ (s) | aveUti (s) | CF*aveUti (s) |
---|---|---|---|---|---|---|---|---|---|
CMRules | 317 | 3.25 (0.84) | 0.58 (0.07) | 0.84 (0.07) | 0.97 (0.04) | -0.04 (0.06) | -0.76 (1.45) | 46196.01 (14527.09) | -1847.84 (2544.18) |
HUSRM | 683 | 10.87 (0.36) | 0.02 (0.01) | 0.76 (0.05) | 1.69 (0.17) | 0.56 (0.11) | 0.59 (0.11) | 1147.04 (104.35) | 642.34 (127.0) |
HAUS-rules | 12 | 3.25 (1.02) | 0.32 (0.16) | 0.95 (0.05) | 1.07 (0.04) | 0.63 (0.28) | 0.63 (0.25) | 26723.55 (14732.57) | 16835.83 (1035.6) |
Synthetic 4
Algorithm | #R | Av_Amp (s) | Av_Sup (s) | Av_Conf (s) | Av_Lift (s) | Av_CF (s) | Av_YulesQ (s) | aveUti (s) | CF*aveUti (s) |
---|---|---|---|---|---|---|---|---|---|
CMRules | 312 | 3.24 (0.84) | 0.58 (0.07) | 0.84 (0.07) | 0.96 (0.04) | -0.04 (0.06) | -0.75 (1.41) | 64400.52 (20438.25) | -2576.02 (3587.99) |
HUSRM | 30214 | 10.88 (0.37) | 0.01 (0.01) | 0.84 (0.11) | 2.07 (0.66) | 0.71 (0.22) | 0.73 (0.22) | 1038.72 (92.04) | 737.49 (220.68) |
HAUS-rules | 12 | 3.42 (0.96) | 0.32 (0.21) | 0.96 (0.03) | 1.06 (0.04) | 0.76 (0.31) | 0.75 (0.27) | 41202.66 (28803.25) | 31314.02 (2665.73) |
Synthetic 5
Algorithm | #R | Av_Amp (s) | Av_Sup (s) | Av_Conf (s) | Av_Lift (s) | Av_CF (s) | Av_YulesQ (s) | aveUti (s) | CF*aveUti (s) |
---|---|---|---|---|---|---|---|---|---|
CMRules | 316 | 3.26 (0.84) | 0.58 (0.07) | 0.84 (0.07) | 0.97 (0.04) | -0.04 (0.06) | -0.77 (1.52) | 92291.01 (29004.59) | -3691.64 (5064.01) |
HUSRM | 13309 | 10.82 (0.45) | 0.01 (0.01) | 0.84 (0.1) | 1.7 (0.39) | 0.66 (0.2) | 0.66 (0.21) | 865.8 (92.44) | 571.43 (172.21) |
HAUS-rules | 13 | 3.16 (1.03) | 0.38 (0.22) | 0.95 (0.04) | 1.06 (0.05) | 0.66 (0.32) | 0.63 (0.37) | 70072.7 (51126.45) | 46247.98 (7010.09) |
Bible
Algorithm | #R | Av_Amp (s) | Av_Sup (s) | Av_Conf (s) | Av_Lift (s) | Av_CF (s) | Av_YulesQ (s) | aveUti (s) | CF*aveUti (s) |
---|---|---|---|---|---|---|---|---|---|
CMRules | 178 | 3.8 (0.99) | 0.03 (0.05) | 0.79 (0.07) | 5.12 (10.92) | 0.48 (0.29) | 0.51 (0.35) | 9841.06 (17278.23) | 4723.71 (2939.89) |
HUSRM | 179 | 5.1 (1.43) | 0.02 (0.05) | 0.83 (0.05) | 9.5 (16.85) | 0.66 (0.21) | 0.71 (0.29) | 6000.85 (16337.95) | 3960.56 (2319.55) |
HAUS-rules | 17 | 3.59 (1.15) | 0.01 (0.02) | 0.71 (0.22) | 11.49 (14.21) | 0.68 (0.24) | 0.76 (0.32) | 2936.12 (3908.47) | 1996.56 (694.15) |
BMS
Algorithm | #R | Av_Amp (s) | Av_Sup (s) | Av_Conf (s) | Av_Lift (s) | Av_CF (s) | Av_YulesQ (s) | aveUti (s) | CF*aveUti (s) |
---|---|---|---|---|---|---|---|---|---|
CMRules | 1 | 2.0 (0.0) | 0.01 (0.0) | 0.79 (0.0) | 12.9 (0.0) | 0.78 (0.0) | 0.98 (0.0) | 9044.0 (0.0) | 7054.32 (0.0) |
HUSRM | 50408 | 10.99 (0.13) | 0.01 (0.01) | 1.0 (0.02) | 63.39 (0.69) | 1.0 (0.02) | 0.0 (0.0) | 699.3 (16.38) | 699.3 (16.38) |
HAUS-rules | 8 | 2.5 (0.71) | 0.01 (0.01) | 0.71 (0.24) | 12.39 (4.4) | 0.69 (0.26) | 0.95 (0.06) | 10326.04 (6133.35) | 7124.97 (1885.01) |
FIFA
Algorithm | #R | Av_Amp (s) | Av_Sup (s) | Av_Conf (s) | Av_Lift (s) | Av_CF (s) | Av_YulesQ (s) | aveUti (s) | CF*aveUti (s) |
---|---|---|---|---|---|---|---|---|---|
CMRules | - | ||||||||
HUSRM | 2959 | 6.82 (0.44) | 0.15 (0.02) | 0.74 (0.03) | 2.13 (0.09) | 0.6 (0.04) | 0.79 (0.03) | 84593.32 (7936.9) | 50755.99 (5345.0) |
HAUS-rules | 43 | 4.17 (1.87) | 0.08 (0.1) | 0.83 (0.06) | 53.93 (135.05) | 0.79 (0.1) | 0.94 (0.16) | 46555.99 (63311.72) | 36779.23 (38653.17) |
Kosarak
Algorithm | #R | Av_Amp (s) | Av_Sup (s) | Av_Conf (s) | Av_Lift (s) | Av_CF (s) | Av_YulesQ (s) | aveUti (s) | CF*aveUti (s) |
---|---|---|---|---|---|---|---|---|---|
CMRules | 66 | 3.46 (0.95) | 0.03 (0.05) | 0.87 (0.09) | 7.84 (4.96) | 0.82 (0.11) | 0.93 (0.12) | 4314.42 (6870.69) | 3537.82 (5036.08) |
HUSRM | 1260 | 9.0 (0.07) | 0.01 (0.01) | 0.72 (0.01) | 1.57 (0.01) | 0.48 (0.01) | 0.0 (0.0) | 147.92 (3.32) | 71.0 (1.58) |
HAUS-rules | 4 | 3.0 (0.71) | 0.13 (0.12) | 0.96 (0.05) | 1.58 (0.07) | 0.89 (0.11) | 0.92 (0.08) | 19975.05 (19581.73) | 17777.79 (13644.25) |
SIGN
Algorithm | #R | Av_Amp (s) | Av_Sup (s) | Av_Conf (s) | Av_Lift (s) | Av_CF (s) | Av_YulesQ (s) | aveUti (s) | CF*aveUti (s) |
---|---|---|---|---|---|---|---|---|---|
CMRules | 1279 | 3.89 (1.01) | 0.48 (0.08) | 0.84 (0.06) | 0.96 (0.06) | -0.04 (0.1) | -0.59 (0.8) | 5904.47 (1803.35) | -236.18 (466.58) |
HUSRM | 181 | 5.3 (1.24) | 0.45 (0.1) | 0.84 (0.05) | 0.95 (0.03) | -0.06 (0.03) | -0.65 (0.51) | 7222.02 (2031.25) | -433.32 (177.74) |
HAUS-rules | 13 | 3.31 (1.14) | 0.33 (0.19) | 0.92 (0.14) | 1.03 (0.08) | 0.45 (0.35) | 0.29 (0.7) | 4900.59 (2922.91) | 2205.27 (1043.85) |
Dataset for the biological problem
The dataset used to extract relevant biological information from a longitudinal intervention in humans can be downloaded by clicking here.
The original dataset was downloaded from the public repository GEO with identifier GSE77962.