Full Result Table for DIGI dataset
You sort the results by clicking on the table headers.
Metrics |
MRR@3 |
MRR@5 |
MRR@10 |
MRR@20 |
HitRate@3 |
HitRate@5 |
HitRate@10 |
HitRate@20 |
Cov@20 |
Pop@20 |
T-time(s) |
P-time (s) |
SFSKNN |
0.322 |
0.337 |
0.348 |
0.351 |
0.413 |
0.480 |
0.559 |
0.604 |
0.072 |
0.071 |
4.895 |
0.006 |
STAN |
0.321 |
0.338 |
0.347 |
0.351 |
0.389 |
0.465 |
0.529 |
0.600 |
0.087 |
0.091 |
2.307 |
0.015 |
VSTAN |
0.317 |
0.332 |
0.342 |
0.346 |
0.383 |
0.449 |
0.520 |
0.581 |
0.086 |
0.084 |
2.709 |
0.014 |
SR |
0.304 |
0.324 |
0.333 |
0.337 |
0.413 |
0.497 |
0.568 |
0.617 |
0.086 |
0.075 |
7.273 |
0.004 |
VSKNN |
0.300 |
0.312 |
0.325 |
0.330 |
0.353 |
0.406 |
0.499 |
0.576 |
0.082 |
0.084 |
9.030 |
0.037 |
COTREC |
0.298 |
0.311 |
0.330 |
0.335 |
0.366 |
0.424 |
0.555 |
0.637 |
0.078 |
0.079 |
28842.562 |
1.992 |
MGS |
0.292 |
0.309 |
0.322 |
0.329 |
0.383 |
0.458 |
0.559 |
0.656 |
0.073 |
0.089 |
23453.641 |
0.016 |
SR-GNN |
0.286 |
0.305 |
0.321 |
0.327 |
0.385 |
0.469 |
0.591 |
0.688 |
0.079 |
0.078 |
3307.174 |
0.027 |
GNRRW |
0.282 |
0.303 |
0.318 |
0.324 |
0.378 |
0.469 |
0.578 |
0.667 |
0.073 |
0.078 |
9279.445 |
0.174 |
CM-HGNN |
0.274 |
0.296 |
0.310 |
0.316 |
0.361 |
0.458 |
0.561 |
0.649 |
0.072 |
0.083 |
56683.551 |
0.013 |
TAGNN |
0.243 |
0.264 |
0.279 |
0.287 |
0.333 |
0.428 |
0.544 |
0.645 |
0.073 |
0.102 |
7189.390 |
0.007 |
GCE-GNN |
0.202 |
0.216 |
0.227 |
0.236 |
0.269 |
0.333 |
0.419 |
0.553 |
0.065 |
0.097 |
69231.684 |
0.503 |
FLCSP |
0.146 |
0.159 |
0.175 |
0.184 |
0.219 |
0.280 |
0.398 |
0.525 |
0.073 |
0.075 |
2449.509 |
0.010 |
Statistical analysis based on MRR@20
We perform a significance test by calculating session-individual metric values e.g.,
obtain the mean MRR values of all sessions in the test data and then use
the ANOVA test to analyze whether the difference between the compared models is significant.
One-way ANOVA
Null hypothesis (Ho): There is no difference in the model means
Alternative hypothesis (H1): At least one model's mean differs from the others
Significance level = 0.05
F-value = 2.509
P-value = 0.004
The P-value is less than the value of of significance level. So, we have enough evidence to reject the Ho.
We now know that at least the mean of a model is different from the others. Therefore, the post hoc analysis was performed using the Tukey test to
determine the mean of which model differs from the others. Our analysis reveals that the following models have different means while others have the same mean.
Moreover, in the first table, we can see that the MRR@20 values of the best performing models e.g., SFSKNN, STAN, VTSAN, SR, MGS and COREC are nearly equal.
Therefore, the ANOVA test reveals that top-performing models do not have significant difference among their mean MRR@20 values.
Note: we report only those cases of the Tukey test where the Ho is rejected.
group1 |
group2 |
meandiff |
p-adj |
lower |
upper |
reject |
FLCSP |
GGNN |
0.0966 |
0.0277 |
0.0052 |
0.188 |
TRUE |
FLCSP |
GNRWW |
0.0941 |
0.0369 |
0.0027 |
0.1855 |
TRUE |
FLCSP |
MGS |
0.0927 |
0.0432 |
0.0013 |
0.1841 |
TRUE |
FLCSP |
sfcknn |
0.1047 |
0.01 |
0.0133 |
0.1961 |
TRUE |
FLCSP |
sr |
0.0921 |
0.0461 |
0.0007 |
0.1835 |
TRUE |
FLCSP |
stan |
0.0953 |
0.0321 |
0.0039 |
0.1867 |
TRUE |
FLCSP |
vstan |
0.0939 |
0.0379 |
0.0025 |
0.1853 |
TRUE |
Statistical values based on MRR@20
- Average: 0.335
- Standard deviation: 0.010
- Minimum value: 0.309
- Maximum value: 0.343
- Difference(%): 3.4
Metrics |
MRR@3: |
MRR@5: |
MRR@10: |
MRR@20: |
HitRate@3: |
HitRate@5: |
HitRate@10: |
HitRate@20: |
embedding_size=16 |
0.276 |
0.289 |
0.302 |
0.310 |
0.335 |
0.396 |
0.495 |
0.596 |
embedding_size=32 |
0.292 |
0.308 |
0.322 |
0.329 |
0.357 |
0.428 |
0.538 |
0.624 |
embedding_size=64 |
0.304 |
0.322 |
0.338 |
0.343 |
0.366 |
0.441 |
0.566 |
0.632 |
embedding_size=80 |
0.303 |
0.319 |
0.335 |
0.340 |
0.374 |
0.447 |
0.557 |
0.632 |
embedding_size=100 |
0.306 |
0.325 |
0.337 |
0.343 |
0.381 |
0.465 |
0.557 |
0.639 |
embedding_size=120 |
0.301 |
0.318 |
0.335 |
0.340 |
0.368 |
0.441 |
0.566 |
0.645 |
embedding_size=150 |
0.300 |
0.314 |
0.329 |
0.337 |
0.372 |
0.437 |
0.553 |
0.654 |
embedding_size=200 |
0.296 |
0.311 |
0.328 |
0.333 |
0.368 |
0.432 |
0.563 |
0.637 |
embedding_size=230 |
0.294 |
0.313 |
0.328 |
0.334 |
0.361 |
0.447 |
0.559 |
0.641 |
embedding_size=250 |
0.306 |
0.321 |
0.337 |
0.343 |
0.376 |
0.445 |
0.563 |
0.647 |
Statistical values based on MRR@20
- Average: 0.336
- Standard deviation: 0.005
- Minimum value: 0.327
- Maximum value: 0.346
- Difference(%): 1.9
Metrics |
MRR@3: |
MRR@5: |
MRR@10: |
MRR@20: |
HitRate@3: |
HitRate@5: |
HitRate@10: |
HitRate@20: |
embedding_size=16 |
0.286 |
0.305 |
0.320 |
0.327 |
0.370 |
0.456 |
0.566 |
0.667 |
embedding_size=32 |
0.303 |
0.320 |
0.334 |
0.342 |
0.402 |
0.475 |
0.581 |
0.684 |
embedding_size=64 |
0.302 |
0.318 |
0.330 |
0.338 |
0.404 |
0.475 |
0.566 |
0.682 |
embedding_size=80 |
0.300 |
0.318 |
0.333 |
0.339 |
0.415 |
0.492 |
0.598 |
0.688 |
embedding_size=100 |
0.295 |
0.313 |
0.328 |
0.335 |
0.391 |
0.467 |
0.583 |
0.686 |
embedding_size=120 |
0.294 |
0.312 |
0.326 |
0.333 |
0.385 |
0.467 |
0.572 |
0.677 |
embedding_size=150 |
0.306 |
0.321 |
0.336 |
0.342 |
0.406 |
0.473 |
0.583 |
0.684 |
embedding_size=200 |
0.296 |
0.314 |
0.328 |
0.335 |
0.402 |
0.477 |
0.585 |
0.682 |
embedding_size=230 |
0.291 |
0.311 |
0.325 |
0.330 |
0.385 |
0.475 |
0.574 |
0.654 |
embedding_size=250 |
0.309 |
0.328 |
0.341 |
0.347 |
0.411 |
0.495 |
0.600 |
0.677 |
Statistical values based on MRR@20
- Average: 0.247
- Standard deviation: 0.033
- Minimum value: 0.164
- Maximum value: 0.294
- Difference(%): 13
Metrics |
MRR@3: |
MRR@5: |
MRR@10: |
MRR@15: |
MRR@20: |
HitRate@3: |
HitRate@5: |
HitRate@10: |
HitRate@20: |
embedding_size=16 |
0.132 |
0.146 |
0.157 |
0.163 |
0.165 |
0.187 |
0.247 |
0.333 |
0.439 |
embedding_size=32 |
0.208 |
0.226 |
0.240 |
0.244 |
0.246 |
0.295 |
0.372 |
0.480 |
0.566 |
embedding_size=64 |
0.255 |
0.276 |
0.289 |
0.293 |
0.294 |
0.344 |
0.434 |
0.535 |
0.617 |
embedding_size=80 |
0.221 |
0.241 |
0.256 |
0.261 |
0.263 |
0.295 |
0.383 |
0.495 |
0.594 |
embedding_size=100 |
0.221 |
0.243 |
0.257 |
0.262 |
0.263 |
0.310 |
0.404 |
0.514 |
0.598 |
embedding_size=120 |
0.203 |
0.219 |
0.235 |
0.240 |
0.242 |
0.288 |
0.359 |
0.473 |
0.581 |
embedding_size=150 |
0.226 |
0.239 |
0.253 |
0.258 |
0.262 |
0.305 |
0.359 |
0.467 |
0.596 |
embedding_size=200 |
0.214 |
0.232 |
0.250 |
0.254 |
0.256 |
0.290 |
0.366 |
0.505 |
0.583 |
embedding_size=230 |
0.206 |
0.226 |
0.240 |
0.244 |
0.247 |
0.299 |
0.383 |
0.490 |
0.587 |
embedding_size=250 |
0.200 |
0.219 |
0.233 |
0.237 |
0.239 |
0.303 |
0.385 |
0.488 |
0.583 |
Statistical values based on MRR@20
- Average: 0.247
- Standard deviation: 0.011
- Minimum value: 0.191
- Maximum value: 0.224
- Difference(%): 3.3
Metrics |
MRR@3: |
MRR@5: |
MRR@10: |
MRR@20: |
HitRate@3: |
HitRate@5: |
HitRate@10: |
HitRate@20: |
embedding_size=16 |
0.175 |
0.188 |
0.200 |
0.207 |
0.245 |
0.303 |
0.396 |
0.492 |
embedding_size=32 |
0.176 |
0.189 |
0.204 |
0.211 |
0.252 |
0.310 |
0.428 |
0.540 |
embedding_size=64 |
0.158 |
0.168 |
0.183 |
0.191 |
0.228 |
0.273 |
0.381 |
0.503 |
embedding_size=80 |
0.174 |
0.186 |
0.202 |
0.209 |
0.258 |
0.312 |
0.432 |
0.527 |
embedding_size=100 |
0.159 |
0.177 |
0.191 |
0.197 |
0.222 |
0.301 |
0.402 |
0.490 |
embedding_size=120 |
0.187 |
0.203 |
0.215 |
0.222 |
0.262 |
0.333 |
0.422 |
0.525 |
embedding_size=150 |
0.165 |
0.182 |
0.195 |
0.203 |
0.234 |
0.310 |
0.398 |
0.516 |
embedding_size=200 |
0.155 |
0.170 |
0.186 |
0.192 |
0.234 |
0.303 |
0.419 |
0.514 |
embedding_size=230 |
0.190 |
0.205 |
0.218 |
0.225 |
0.265 |
0.329 |
0.430 |
0.529 |
embedding_size=250 |
0.163 |
0.183 |
0.198 |
0.205 |
0.228 |
0.316 |
0.415 |
0.523 |
Statistical values based on MRR@20
- Average: 0.313
- Standard deviation: 0.008
- Minimum value: 0.296
- Maximum value: 0.324
- Difference(%): 2.8
Metrics |
MRR@3: |
MRR@5: |
MRR@10: |
MRR@20: |
HitRate@3: |
HitRate@5: |
HitRate@10: |
HitRate@20: |
embedding_size=16 |
0.257 |
0.277 |
0.289 |
0.297 |
0.361 |
0.447 |
0.540 |
0.654 |
embedding_size=32 |
0.272 |
0.291 |
0.307 |
0.314 |
0.372 |
0.456 |
0.576 |
0.675 |
embedding_size=64 |
0.269 |
0.289 |
0.304 |
0.312 |
0.378 |
0.465 |
0.578 |
0.688 |
embedding_size=80 |
0.287 |
0.306 |
0.318 |
0.324 |
0.389 |
0.473 |
0.563 |
0.656 |
embedding_size=100 |
0.272 |
0.289 |
0.304 |
0.311 |
0.372 |
0.452 |
0.566 |
0.671 |
embedding_size=120 |
0.270 |
0.291 |
0.303 |
0.310 |
0.383 |
0.475 |
0.568 |
0.669 |
embedding_size=150 |
0.271 |
0.292 |
0.307 |
0.313 |
0.368 |
0.462 |
0.572 |
0.660 |
embedding_size=200 |
0.284 |
0.300 |
0.315 |
0.321 |
0.394 |
0.469 |
0.576 |
0.667 |
embedding_size=230 |
0.276 |
0.294 |
0.311 |
0.318 |
0.378 |
0.460 |
0.587 |
0.680 |
embedding_size=250 |
0.279 |
0.295 |
0.309 |
0.315 |
0.394 |
0.462 |
0.572 |
0.660 |
Statistical analysis based on MRR@20
COTREC |
GNRWW |
TAGNN |
FLCSP |
GGNN |
0.310 |
0.327 |
0.165 |
0.207 |
0.297 |
0.329 |
0.342 |
0.246 |
0.211 |
0.314 |
0.343 |
0.338 |
0.294 |
0.191 |
0.312 |
0.340 |
0.339 |
0.263 |
0.209 |
0.324 |
0.343 |
0.335 |
0.263 |
0.197 |
0.311 |
0.340 |
0.333 |
0.242 |
0.222 |
0.310 |
0.337 |
0.342 |
0.262 |
0.203 |
0.313 |
0.333 |
0.335 |
0.256 |
0.192 |
0.321 |
0.334 |
0.330 |
0.247 |
0.225 |
0.318 |
0.343 |
0.347 |
0.239 |
0.205 |
0.315 |
One-way ANOVA
Null hypothesis (Ho): There is no difference in the model means UCOTREC = UGNRWW = UTAGNN = UFLCSP = UGGNN
Alternative hypothesis (H1): At least one model's mean differs from the others
Significance level = 0.05
Summary |
Groups |
Count |
Sum |
Average |
Variance |
COTREC |
10 |
3.350865671 |
0.3350865671 |
0.0001032043935 |
GNRWW |
10 |
3.368446379 |
0.3368446379 |
0.00003443092133 |
TAGNN |
10 |
2.476281933 |
0.2476281933 |
0.0010992159 |
FLCSP |
10 |
2.062314624 |
0.2062314624 |
0.0001282693332 |
GGNN |
10 |
3.135340815 |
0.3135340815 |
0.00005413629124 |
ANOVA |
Source of Variation |
SS |
df |
MS |
F-value |
P-value |
F(critical) |
Between Groups |
0.1357081815 |
4 |
0.03392704538 |
119.5239806 |
0 |
2.578739184 |
Within Groups |
0.01277331155 |
45 |
0.0002838513678 |
Total |
0.1484814931 |
49 |
The F-value and critical F- value are 119.523 and 2.578, respectively. The F-value is greater than the critical F-value, therefore, we reject the Ho.
The main purpose of the ANOVA test is to observe the variability between the groups/compared models. However, it does not explain about the magnitude of variability.
Therefore, we use the effect size (η) to know the magnitude of variability between the models. The effect size uses the following table to explain the level of variability.
η |
Size |
0.01 |
small |
0.09 |
medium |
0.25 |
large |
Note: if less than .01, no effect is reported |
η = 0.135708181506113 / 0.148481493058201
η = 0.9139
Here we observe the large effect size between the GNN models.
References:
- https://open.maricopa.edu/psy230mm/chapter/chapter-14-analysis-of-variance/
- https://en.wikipedia.org/wiki/Analysis_of_variance
Statistical values based on MRR@20
- Average: 0.337
- Standard deviation: 0.003
- Minimum value: 0.329
- Maximum value: 0.343
- Difference(%): 1.4
MRR@20 varies across of random seeds
Metrics |
MRR@3: |
MRR@5: |
MRR@10: |
MRR@20: |
HitRate@3: |
HitRate@5: |
HitRate@10: |
HitRate@20: |
seed=1996073 |
0.305 |
0.320 |
0.336 |
0.341 |
0.374 |
0.441 |
0.559 |
0.632 |
seed=854750 |
0.301 |
0.318 |
0.332 |
0.338 |
0.368 |
0.443 |
0.551 |
0.628 |
seed=888529 |
0.300 |
0.314 |
0.330 |
0.336 |
0.372 |
0.432 |
0.553 |
0.630 |
seed=1184622 |
0.301 |
0.312 |
0.330 |
0.336 |
0.374 |
0.424 |
0.548 |
0.645 |
seed=17829 |
0.303 |
0.318 |
0.333 |
0.340 |
0.376 |
0.441 |
0.548 |
0.634 |
seed=1830297 |
0.305 |
0.321 |
0.337 |
0.342 |
0.374 |
0.447 |
0.568 |
0.634 |
seed=2143189 |
0.297 |
0.315 |
0.330 |
0.336 |
0.366 |
0.439 |
0.551 |
0.637 |
seed=2286376 |
0.290 |
0.309 |
0.325 |
0.329 |
0.355 |
0.441 |
0.557 |
0.626 |
seed=174185 |
0.299 |
0.318 |
0.334 |
0.339 |
0.368 |
0.454 |
0.566 |
0.637 |
seed=2056912 |
0.302 |
0.317 |
0.332 |
0.338 |
0.376 |
0.443 |
0.551 |
0.637 |
seed=2634968 |
0.303 |
0.318 |
0.335 |
0.341 |
0.366 |
0.434 |
0.555 |
0.643 |
seed=804381 |
0.299 |
0.319 |
0.332 |
0.339 |
0.363 |
0.454 |
0.551 |
0.639 |
seed=1918225 |
0.300 |
0.317 |
0.333 |
0.339 |
0.366 |
0.439 |
0.559 |
0.637 |
seed=2054242 |
0.301 |
0.316 |
0.331 |
0.338 |
0.370 |
0.432 |
0.546 |
0.639 |
seed=2698057 |
0.301 |
0.316 |
0.334 |
0.339 |
0.368 |
0.430 |
0.566 |
0.634 |
seed=2973600 |
0.304 |
0.319 |
0.334 |
0.341 |
0.376 |
0.441 |
0.548 |
0.647 |
seed=1386487 |
0.311 |
0.323 |
0.338 |
0.344 |
0.387 |
0.443 |
0.555 |
0.632 |
seed=2765375 |
0.300 |
0.316 |
0.334 |
0.338 |
0.363 |
0.439 |
0.568 |
0.634 |
seed=2754545 |
0.291 |
0.313 |
0.327 |
0.333 |
0.353 |
0.452 |
0.553 |
0.634 |
seed=204245 |
0.304 |
0.319 |
0.333 |
0.339 |
0.381 |
0.447 |
0.553 |
0.639 |
seed=770362 |
0.299 |
0.313 |
0.330 |
0.336 |
0.368 |
0.426 |
0.555 |
0.639 |
seed=1274950 |
0.300 |
0.317 |
0.332 |
0.338 |
0.363 |
0.439 |
0.546 |
0.639 |
seed=2920651 |
0.300 |
0.317 |
0.332 |
0.338 |
0.366 |
0.439 |
0.553 |
0.634 |
seed=2874302 |
0.301 |
0.320 |
0.335 |
0.340 |
0.366 |
0.452 |
0.555 |
0.630 |
seed=1526224 |
0.296 |
0.314 |
0.330 |
0.336 |
0.363 |
0.443 |
0.557 |
0.637 |
seed=1287909 |
0.303 |
0.323 |
0.336 |
0.342 |
0.372 |
0.462 |
0.557 |
0.645 |
seed=1536514 |
0.297 |
0.315 |
0.330 |
0.336 |
0.357 |
0.434 |
0.553 |
0.632 |
seed=1202831 |
0.304 |
0.319 |
0.336 |
0.342 |
0.370 |
0.439 |
0.561 |
0.641 |
seed=424710 |
0.299 |
0.314 |
0.329 |
0.335 |
0.376 |
0.443 |
0.557 |
0.632 |
seed=2050972 |
0.295 |
0.311 |
0.325 |
0.331 |
0.368 |
0.443 |
0.548 |
0.634 |
seed=608005 |
0.301 |
0.319 |
0.332 |
0.339 |
0.366 |
0.445 |
0.540 |
0.641 |
seed=831980 |
0.300 |
0.317 |
0.333 |
0.339 |
0.361 |
0.434 |
0.555 |
0.634 |
seed=1798918 |
0.293 |
0.312 |
0.327 |
0.333 |
0.359 |
0.441 |
0.561 |
0.634 |
seed=384211 |
0.303 |
0.322 |
0.335 |
0.340 |
0.366 |
0.452 |
0.553 |
0.634 |
Statistical values based on MRR@20
- Average: 0.340
- Standard deviation: 0.006
- Minimum value: 0.327
- Maximum value: 0.352
- Difference(%): 2.5
MRR@20 varies across of random seeds
Metrics |
MRR@3: |
MRR@5: |
MRR@10: |
MRR@20: |
HitRate@3: |
HitRate@5: |
HitRate@10: |
HitRate@20: |
seed=1447236 |
0.299 |
0.315 |
0.329 |
0.336 |
0.398 |
0.471 |
0.576 |
0.671 |
seed=1304289 |
0.298 |
0.320 |
0.333 |
0.340 |
0.383 |
0.480 |
0.581 |
0.684 |
seed=87127 |
0.292 |
0.312 |
0.328 |
0.334 |
0.378 |
0.469 |
0.581 |
0.665 |
seed=1881266 |
0.296 |
0.316 |
0.332 |
0.339 |
0.385 |
0.473 |
0.594 |
0.697 |
seed=2840823 |
0.291 |
0.312 |
0.325 |
0.332 |
0.387 |
0.475 |
0.574 |
0.673 |
seed=1851086 |
0.302 |
0.318 |
0.334 |
0.341 |
0.389 |
0.456 |
0.581 |
0.675 |
seed=1075394 |
0.304 |
0.319 |
0.334 |
0.342 |
0.396 |
0.462 |
0.570 |
0.673 |
seed=493588 |
0.297 |
0.314 |
0.331 |
0.337 |
0.391 |
0.462 |
0.594 |
0.680 |
seed=1592372 |
0.306 |
0.329 |
0.341 |
0.348 |
0.387 |
0.486 |
0.574 |
0.675 |
seed=167556 |
0.306 |
0.323 |
0.338 |
0.345 |
0.394 |
0.465 |
0.585 |
0.697 |
seed=2886392 |
0.296 |
0.315 |
0.327 |
0.334 |
0.394 |
0.475 |
0.568 |
0.675 |
seed=712613 |
0.307 |
0.322 |
0.336 |
0.344 |
0.400 |
0.462 |
0.570 |
0.673 |
seed=803331 |
0.310 |
0.328 |
0.342 |
0.348 |
0.398 |
0.475 |
0.583 |
0.671 |
seed=738772 |
0.296 |
0.314 |
0.328 |
0.335 |
0.394 |
0.475 |
0.572 |
0.675 |
seed=628465 |
0.296 |
0.314 |
0.328 |
0.335 |
0.387 |
0.462 |
0.572 |
0.667 |
seed=2958120 |
0.303 |
0.319 |
0.333 |
0.342 |
0.396 |
0.465 |
0.563 |
0.690 |
seed=207155 |
0.301 |
0.317 |
0.331 |
0.338 |
0.391 |
0.462 |
0.561 |
0.669 |
seed=1096544 |
0.297 |
0.318 |
0.332 |
0.339 |
0.381 |
0.471 |
0.578 |
0.680 |
seed=1746569 |
0.317 |
0.332 |
0.346 |
0.353 |
0.415 |
0.482 |
0.589 |
0.686 |
seed=420360 |
0.308 |
0.326 |
0.337 |
0.345 |
0.402 |
0.480 |
0.568 |
0.673 |
seed=48698 |
0.306 |
0.321 |
0.335 |
0.343 |
0.400 |
0.462 |
0.570 |
0.684 |
seed=2866263 |
0.292 |
0.310 |
0.325 |
0.333 |
0.381 |
0.458 |
0.561 |
0.673 |
seed=2588109 |
0.307 |
0.328 |
0.337 |
0.346 |
0.391 |
0.484 |
0.557 |
0.677 |
seed=2442223 |
0.307 |
0.323 |
0.337 |
0.343 |
0.396 |
0.465 |
0.572 |
0.662 |
seed=2795284 |
0.289 |
0.308 |
0.320 |
0.328 |
0.387 |
0.467 |
0.563 |
0.673 |
seed=2083911 |
0.306 |
0.322 |
0.337 |
0.343 |
0.394 |
0.467 |
0.572 |
0.660 |
seed=1226771 |
0.306 |
0.323 |
0.335 |
0.342 |
0.404 |
0.482 |
0.574 |
0.667 |
seed=2477232 |
0.312 |
0.329 |
0.344 |
0.349 |
0.400 |
0.475 |
0.585 |
0.667 |
seed=127267 |
0.310 |
0.330 |
0.345 |
0.351 |
0.383 |
0.473 |
0.591 |
0.675 |
seed=895429 |
0.287 |
0.308 |
0.323 |
0.330 |
0.378 |
0.473 |
0.578 |
0.684 |
seed=1299549 |
0.306 |
0.325 |
0.341 |
0.346 |
0.400 |
0.482 |
0.598 |
0.673 |
seed=477658 |
0.309 |
0.326 |
0.342 |
0.350 |
0.387 |
0.460 |
0.583 |
0.688 |
seed=700523 |
0.299 |
0.314 |
0.330 |
0.336 |
0.389 |
0.454 |
0.578 |
0.671 |
seed=1974593 |
0.300 |
0.321 |
0.333 |
0.340 |
0.400 |
0.492 |
0.583 |
0.684 |
seed=851690 |
0.297 |
0.317 |
0.328 |
0.336 |
0.394 |
0.480 |
0.563 |
0.677 |
seed=1957974 |
0.299 |
0.318 |
0.331 |
0.338 |
0.389 |
0.473 |
0.572 |
0.665 |
seed=2553520 |
0.296 |
0.314 |
0.329 |
0.338 |
0.387 |
0.465 |
0.574 |
0.690 |
seed=2047942 |
0.292 |
0.310 |
0.326 |
0.333 |
0.376 |
0.456 |
0.570 |
0.677 |
seed=1995953 |
0.303 |
0.319 |
0.332 |
0.340 |
0.402 |
0.473 |
0.572 |
0.680 |
seed=1785178 |
0.314 |
0.332 |
0.343 |
0.351 |
0.398 |
0.477 |
0.561 |
0.673 |
seed=123577 |
0.305 |
0.324 |
0.338 |
0.346 |
0.387 |
0.471 |
0.581 |
0.684 |
seed=402210 |
0.302 |
0.324 |
0.338 |
0.346 |
0.374 |
0.471 |
0.570 |
0.682 |
seed=709883 |
0.293 |
0.312 |
0.327 |
0.334 |
0.378 |
0.458 |
0.570 |
0.669 |
seed=534417 |
0.295 |
0.315 |
0.329 |
0.336 |
0.389 |
0.480 |
0.585 |
0.675 |
seed=1919455 |
0.296 |
0.315 |
0.329 |
0.336 |
0.381 |
0.467 |
0.568 |
0.665 |
seed=138216 |
0.299 |
0.317 |
0.332 |
0.338 |
0.389 |
0.471 |
0.583 |
0.675 |
seed=1682370 |
0.312 |
0.328 |
0.341 |
0.348 |
0.411 |
0.482 |
0.578 |
0.680 |
seed=252274 |
0.314 |
0.331 |
0.346 |
0.353 |
0.404 |
0.477 |
0.583 |
0.686 |
seed=917448 |
0.304 |
0.321 |
0.337 |
0.344 |
0.394 |
0.465 |
0.587 |
0.675 |
seed=2813644 |
0.296 |
0.319 |
0.331 |
0.338 |
0.394 |
0.495 |
0.581 |
0.688 |
Statistical values based on MRR@20
- Average: 0.256
- Standard deviation: 0.015
- Minimum value: 0.228
- Maximum value: 0.281
- Difference(%): 5.2
MRR@20 varies across of random seeds
Metrics |
MRR@3: |
MRR@5: |
MRR@10: |
MRR@20: |
HitRate@3: |
HitRate@5: |
HitRate@10: |
HitRate@20: |
seed=2156700 |
0.199 |
0.218 |
0.235 |
0.241 |
0.292 |
0.378 |
0.505 |
0.589 |
seed=2625800 |
0.219 |
0.246 |
0.261 |
0.267 |
0.310 |
0.426 |
0.533 |
0.626 |
seed=1019900 |
0.233 |
0.250 |
0.264 |
0.272 |
0.314 |
0.389 |
0.497 |
0.606 |
seed=1169800 |
0.201 |
0.220 |
0.240 |
0.247 |
0.284 |
0.366 |
0.505 |
0.604 |
seed=8510500 |
0.204 |
0.216 |
0.237 |
0.244 |
0.286 |
0.338 |
0.492 |
0.596 |
seed=3405000 |
0.197 |
0.220 |
0.234 |
0.241 |
0.301 |
0.400 |
0.503 |
0.606 |
seed=7621100 |
0.192 |
0.212 |
0.227 |
0.234 |
0.282 |
0.370 |
0.480 |
0.581 |
seed=6717900 |
0.228 |
0.244 |
0.259 |
0.266 |
0.308 |
0.378 |
0.495 |
0.594 |
seed=4359300 |
0.207 |
0.224 |
0.243 |
0.249 |
0.284 |
0.361 |
0.503 |
0.596 |
seed=6402500 |
0.225 |
0.242 |
0.258 |
0.266 |
0.310 |
0.385 |
0.508 |
0.619 |
seed=374300 |
0.232 |
0.246 |
0.263 |
0.268 |
0.331 |
0.391 |
0.514 |
0.585 |
seed=1765400 |
0.202 |
0.221 |
0.233 |
0.240 |
0.288 |
0.374 |
0.462 |
0.572 |
seed=7477300 |
0.232 |
0.254 |
0.267 |
0.275 |
0.323 |
0.417 |
0.516 |
0.626 |
seed=2982000 |
0.225 |
0.245 |
0.260 |
0.267 |
0.318 |
0.406 |
0.516 |
0.632 |
seed=7066500 |
0.229 |
0.242 |
0.261 |
0.270 |
0.318 |
0.374 |
0.520 |
0.641 |
seed=7864000 |
0.216 |
0.235 |
0.250 |
0.257 |
0.292 |
0.376 |
0.488 |
0.589 |
seed=1964600 |
0.203 |
0.221 |
0.235 |
0.242 |
0.303 |
0.383 |
0.490 |
0.594 |
seed=9114700 |
0.233 |
0.247 |
0.261 |
0.268 |
0.303 |
0.366 |
0.475 |
0.570 |
seed=9102300 |
0.200 |
0.216 |
0.231 |
0.240 |
0.280 |
0.348 |
0.465 |
0.587 |
seed=5097000 |
0.200 |
0.218 |
0.235 |
0.243 |
0.282 |
0.361 |
0.477 |
0.596 |
seed=9151700 |
0.233 |
0.255 |
0.269 |
0.277 |
0.318 |
0.415 |
0.523 |
0.630 |
seed=5503200 |
0.220 |
0.235 |
0.251 |
0.258 |
0.297 |
0.361 |
0.482 |
0.583 |
seed=5008900 |
0.225 |
0.241 |
0.258 |
0.265 |
0.320 |
0.391 |
0.512 |
0.615 |
seed=9707200 |
0.186 |
0.201 |
0.218 |
0.228 |
0.275 |
0.342 |
0.471 |
0.615 |
seed=5080000 |
0.242 |
0.263 |
0.273 |
0.281 |
0.333 |
0.426 |
0.503 |
0.606 |
Statistical values based on MRR@20
- Average: 0.203
- Standard deviation: 0.009
- Minimum value: 0.172
- Maximum value: 0.217
- Difference(%): 4.5
MRR@20 varies across of random seeds
Metrics |
MRR@3: |
MRR@5: |
MRR@10: |
MRR@20: |
HitRate@3: |
HitRate@5: |
HitRate@10: |
HitRate@20: |
seed=851200 |
0.163 |
0.185 |
0.200 |
0.207 |
0.222 |
0.316 |
0.437 |
0.533 |
seed=3238900 |
0.176 |
0.193 |
0.207 |
0.215 |
0.245 |
0.316 |
0.424 |
0.531 |
seed=2971600 |
0.165 |
0.180 |
0.195 |
0.203 |
0.226 |
0.290 |
0.406 |
0.525 |
seed=1863000 |
0.166 |
0.181 |
0.195 |
0.204 |
0.239 |
0.303 |
0.406 |
0.531 |
seed=6541600 |
0.163 |
0.182 |
0.198 |
0.207 |
0.215 |
0.299 |
0.415 |
0.544 |
seed=3411300 |
0.162 |
0.180 |
0.195 |
0.203 |
0.237 |
0.316 |
0.426 |
0.538 |
seed=4766000 |
0.165 |
0.182 |
0.195 |
0.202 |
0.237 |
0.312 |
0.411 |
0.520 |
seed=3108300 |
0.160 |
0.180 |
0.193 |
0.202 |
0.228 |
0.318 |
0.417 |
0.542 |
seed=3605600 |
0.160 |
0.173 |
0.186 |
0.194 |
0.222 |
0.277 |
0.376 |
0.501 |
seed=7563200 |
0.177 |
0.193 |
0.206 |
0.216 |
0.254 |
0.323 |
0.419 |
0.553 |
seed=7407300 |
0.175 |
0.192 |
0.207 |
0.214 |
0.239 |
0.316 |
0.428 |
0.525 |
seed=5491200 |
0.162 |
0.179 |
0.190 |
0.200 |
0.243 |
0.316 |
0.400 |
0.555 |
seed=7271100 |
0.166 |
0.180 |
0.196 |
0.203 |
0.237 |
0.299 |
0.415 |
0.527 |
seed=9514600 |
0.151 |
0.171 |
0.184 |
0.191 |
0.228 |
0.312 |
0.411 |
0.518 |
seed=5767800 |
0.166 |
0.179 |
0.191 |
0.199 |
0.243 |
0.303 |
0.391 |
0.505 |
seed=6856200 |
0.153 |
0.173 |
0.184 |
0.194 |
0.222 |
0.308 |
0.394 |
0.533 |
seed=2725700 |
0.155 |
0.168 |
0.181 |
0.189 |
0.222 |
0.282 |
0.381 |
0.505 |
seed=4395900 |
0.179 |
0.197 |
0.210 |
0.217 |
0.249 |
0.331 |
0.428 |
0.525 |
seed=8766000 |
0.162 |
0.178 |
0.192 |
0.200 |
0.224 |
0.295 |
0.406 |
0.518 |
seed=3461600 |
0.167 |
0.189 |
0.201 |
0.208 |
0.234 |
0.329 |
0.422 |
0.531 |
seed=3184400 |
0.172 |
0.185 |
0.200 |
0.210 |
0.234 |
0.288 |
0.404 |
0.548 |
seed=4451000 |
0.155 |
0.172 |
0.186 |
0.192 |
0.217 |
0.288 |
0.394 |
0.482 |
seed=2861600 |
0.177 |
0.191 |
0.207 |
0.214 |
0.241 |
0.303 |
0.424 |
0.527 |
seed=3847600 |
0.173 |
0.188 |
0.203 |
0.212 |
0.243 |
0.308 |
0.426 |
0.546 |
seed=9242000 |
0.153 |
0.167 |
0.183 |
0.191 |
0.224 |
0.286 |
0.404 |
0.512 |
seed=5152200 |
0.176 |
0.189 |
0.205 |
0.214 |
0.245 |
0.299 |
0.426 |
0.553 |
seed=8868300 |
0.129 |
0.147 |
0.163 |
0.172 |
0.181 |
0.262 |
0.383 |
0.520 |
seed=6399100 |
0.175 |
0.191 |
0.204 |
0.213 |
0.254 |
0.323 |
0.424 |
0.544 |
seed=602300 |
0.164 |
0.177 |
0.192 |
0.197 |
0.254 |
0.312 |
0.424 |
0.508 |
seed=8556600 |
0.168 |
0.182 |
0.195 |
0.204 |
0.243 |
0.303 |
0.409 |
0.531 |
seed=900000 |
0.158 |
0.177 |
0.189 |
0.198 |
0.243 |
0.323 |
0.417 |
0.538 |
seed=724600 |
0.154 |
0.169 |
0.184 |
0.192 |
0.217 |
0.280 |
0.396 |
0.505 |
seed=8223300 |
0.155 |
0.171 |
0.185 |
0.193 |
0.217 |
0.288 |
0.396 |
0.510 |
seed=2641400 |
0.165 |
0.181 |
0.195 |
0.205 |
0.230 |
0.303 |
0.409 |
0.557 |
seed=8817900 |
0.174 |
0.193 |
0.208 |
0.217 |
0.237 |
0.318 |
0.437 |
0.557 |
seed=4217200 |
0.168 |
0.182 |
0.197 |
0.206 |
0.239 |
0.301 |
0.413 |
0.538 |
seed=9522300 |
0.159 |
0.177 |
0.191 |
0.199 |
0.215 |
0.290 |
0.394 |
0.523 |
seed=3571000 |
0.167 |
0.183 |
0.195 |
0.203 |
0.241 |
0.310 |
0.400 |
0.512 |
seed=6604100 |
0.157 |
0.174 |
0.187 |
0.196 |
0.239 |
0.316 |
0.413 |
0.555 |
seed=2226700 |
0.174 |
0.189 |
0.201 |
0.209 |
0.254 |
0.320 |
0.406 |
0.527 |
seed=740400 |
0.173 |
0.190 |
0.203 |
0.211 |
0.247 |
0.320 |
0.426 |
0.535 |
seed=7336000 |
0.169 |
0.187 |
0.202 |
0.209 |
0.237 |
0.314 |
0.426 |
0.527 |
seed=2197700 |
0.160 |
0.183 |
0.196 |
0.205 |
0.230 |
0.329 |
0.426 |
0.563 |
seed=5396900 |
0.175 |
0.189 |
0.200 |
0.209 |
0.265 |
0.331 |
0.415 |
0.538 |
seed=3416000 |
0.160 |
0.180 |
0.189 |
0.198 |
0.232 |
0.318 |
0.389 |
0.518 |
seed=1039800 |
0.162 |
0.179 |
0.193 |
0.199 |
0.228 |
0.301 |
0.411 |
0.501 |
seed=4015400 |
0.154 |
0.176 |
0.188 |
0.196 |
0.219 |
0.312 |
0.402 |
0.516 |
seed=5080900 |
0.154 |
0.174 |
0.188 |
0.196 |
0.222 |
0.305 |
0.419 |
0.525 |
seed=9209300 |
0.179 |
0.198 |
0.210 |
0.216 |
0.247 |
0.329 |
0.424 |
0.512 |
seed=3671400 |
0.171 |
0.190 |
0.203 |
0.211 |
0.234 |
0.316 |
0.417 |
0.523 |
Statistical values based on MRR@20
- Average: 0.322
- Standard deviation: 0.009
- Minimum value: 0.307
- Maximum value: 0.342
- Difference(%):3.5
MRR@20 varies across of random seeds
Metrics |
MRR@3: |
MRR@5: |
MRR@10: |
MRR@20: |
HitRate@3: |
HitRate@5: |
HitRate@10: |
HitRate@20: |
seed=4116600 |
0.278 |
0.299 |
0.314 |
0.322 |
0.381 |
0.469 |
0.585 |
0.690 |
seed=1448500 |
0.275 |
0.297 |
0.313 |
0.320 |
0.359 |
0.458 |
0.578 |
0.677 |
seed=5464300 |
0.274 |
0.292 |
0.307 |
0.315 |
0.383 |
0.462 |
0.578 |
0.692 |
seed=8419700 |
0.281 |
0.302 |
0.320 |
0.327 |
0.376 |
0.465 |
0.600 |
0.708 |
seed=5415500 |
0.261 |
0.285 |
0.302 |
0.309 |
0.359 |
0.465 |
0.585 |
0.686 |
seed=5744100 |
0.279 |
0.303 |
0.316 |
0.322 |
0.394 |
0.497 |
0.596 |
0.680 |
seed=5835200 |
0.277 |
0.301 |
0.314 |
0.322 |
0.376 |
0.480 |
0.581 |
0.692 |
seed=7885800 |
0.287 |
0.303 |
0.319 |
0.326 |
0.391 |
0.465 |
0.583 |
0.677 |
seed=1751600 |
0.283 |
0.303 |
0.319 |
0.327 |
0.378 |
0.465 |
0.589 |
0.690 |
seed=393300 |
0.290 |
0.308 |
0.319 |
0.328 |
0.398 |
0.480 |
0.566 |
0.690 |
seed=9353400 |
0.289 |
0.306 |
0.322 |
0.331 |
0.385 |
0.462 |
0.585 |
0.705 |
seed=8454600 |
0.296 |
0.314 |
0.330 |
0.337 |
0.391 |
0.469 |
0.587 |
0.690 |
seed=8112600 |
0.265 |
0.285 |
0.303 |
0.310 |
0.353 |
0.441 |
0.578 |
0.669 |
seed=2880500 |
0.267 |
0.284 |
0.300 |
0.308 |
0.383 |
0.458 |
0.574 |
0.690 |
seed=4272900 |
0.288 |
0.307 |
0.322 |
0.331 |
0.378 |
0.462 |
0.570 |
0.692 |
seed=5626300 |
0.277 |
0.294 |
0.309 |
0.316 |
0.387 |
0.462 |
0.570 |
0.673 |
seed=5732000 |
0.291 |
0.311 |
0.325 |
0.332 |
0.387 |
0.480 |
0.589 |
0.686 |
seed=7404800 |
0.300 |
0.321 |
0.334 |
0.341 |
0.389 |
0.484 |
0.587 |
0.677 |
seed=1919800 |
0.277 |
0.294 |
0.312 |
0.319 |
0.378 |
0.454 |
0.581 |
0.682 |
seed=3354400 |
0.276 |
0.296 |
0.315 |
0.320 |
0.372 |
0.458 |
0.602 |
0.682 |
seed=1685800 |
0.303 |
0.319 |
0.333 |
0.340 |
0.400 |
0.469 |
0.576 |
0.669 |
seed=8395700 |
0.279 |
0.299 |
0.314 |
0.321 |
0.387 |
0.473 |
0.587 |
0.686 |
seed=1208800 |
0.270 |
0.287 |
0.303 |
0.311 |
0.381 |
0.458 |
0.578 |
0.695 |
seed=3102900 |
0.283 |
0.303 |
0.320 |
0.326 |
0.372 |
0.460 |
0.585 |
0.667 |
seed=3163100 |
0.269 |
0.290 |
0.306 |
0.313 |
0.368 |
0.460 |
0.574 |
0.673 |
seed=5601800 |
0.290 |
0.310 |
0.323 |
0.329 |
0.394 |
0.477 |
0.578 |
0.667 |
seed=151700 |
0.263 |
0.284 |
0.301 |
0.308 |
0.368 |
0.456 |
0.578 |
0.682 |
seed=5621500 |
0.259 |
0.281 |
0.300 |
0.307 |
0.348 |
0.447 |
0.587 |
0.686 |
seed=2264600 |
0.287 |
0.304 |
0.319 |
0.325 |
0.398 |
0.473 |
0.591 |
0.677 |
seed=3172900 |
0.280 |
0.298 |
0.315 |
0.322 |
0.385 |
0.465 |
0.591 |
0.697 |
seed=5694900 |
0.282 |
0.299 |
0.315 |
0.322 |
0.389 |
0.467 |
0.578 |
0.686 |
seed=3813500 |
0.281 |
0.305 |
0.323 |
0.329 |
0.374 |
0.482 |
0.609 |
0.699 |
seed=8295000 |
0.270 |
0.297 |
0.311 |
0.318 |
0.357 |
0.473 |
0.581 |
0.671 |
seed=5495900 |
0.277 |
0.295 |
0.314 |
0.321 |
0.368 |
0.445 |
0.589 |
0.692 |
seed=7106200 |
0.302 |
0.318 |
0.336 |
0.342 |
0.404 |
0.477 |
0.613 |
0.705 |
Statistical analysis based on MRR@20
COTREC |
GNRRW |
TAGNN |
FLCSP |
GGNN |
0.3409937 |
0.33599206 |
0.2409126 |
0.2065565 |
0.3218514 |
0.3376615 |
0.34049176 |
0.2671731 |
0.2150780 |
0.3196387 |
0.3360568 |
0.33384089 |
0.2719202 |
0.2032149 |
0.3150520 |
0.3364039 |
0.33920997 |
0.2466212 |
0.2038967 |
0.3270256 |
0.3395593 |
0.33225052 |
0.2441588 |
0.2071149 |
0.3085969 |
0.3417518 |
0.34050359 |
0.2408133 |
0.2030578 |
0.3219477 |
0.3358070 |
0.34157847 |
0.2343214 |
0.2023181 |
0.3219050 |
0.3294316 |
0.33690436 |
0.2658386 |
0.2021730 |
0.3257824 |
0.3385516 |
0.34753455 |
0.2494611 |
0.1944837 |
0.3266497 |
0.3379797 |
0.34518535 |
0.2662642 |
0.2156291 |
0.3278797 |
0.3405640 |
0.33449492 |
0.2681523 |
0.2141539 |
0.3308277 |
0.3385499 |
0.34387576 |
0.2400835 |
0.2003993 |
0.3369646 |
0.3385337 |
0.34791349 |
0.2747149 |
0.2031463 |
0.3096330 |
0.3376391 |
0.33509712 |
0.2674166 |
0.1910997 |
0.3084844 |
0.3392099 |
0.33452941 |
0.2699714 |
0.1991495 |
0.3305054 |
0.3409725 |
0.34168398 |
0.2573615 |
0.1941384 |
0.3159991 |
0.3439723 |
0.33834337 |
0.2423687 |
0.1894486 |
0.3318970 |
0.3382212 |
0.33945972 |
0.2679075 |
0.2170486 |
0.3408552 |
0.3327706 |
0.35296907 |
0.2401311 |
0.1999889 |
0.3188616 |
0.3386084 |
0.34456512 |
0.2427355 |
0.2084436 |
0.3202280 |
0.3359206 |
0.34302696 |
0.2766572 |
0.2101228 |
0.3398760 |
0.3381904 |
0.33284777 |
0.2577398 |
0.1916497 |
0.3208971 |
0.3378326 |
0.34612621 |
0.2649578 |
0.2138115 |
0.3110524 |
0.3400954 |
0.34324776 |
0.2280838 |
0.2120328 |
0.3260680 |
0.3355072 |
0.32798605 |
0.2805328 |
0.1907867 |
0.3131729 |
0.3420006 |
0.34320468 |
|
0.2141117 |
0.3291776 |
0.3361578 |
0.34163871 |
|
0.1721716 |
0.3079964 |
0.3419555 |
0.34923896 |
|
0.2126700 |
0.3072804 |
0.3349865 |
0.35120298 |
|
0.1974497 |
0.3251047 |
0.3313467 |
0.32971577 |
|
0.2041034 |
0.3220460 |
0.3392978 |
0.34585229 |
|
0.1975199 |
0.3219706 |
0.3388039 |
0.34994560 |
|
0.1921189 |
0.3290076 |
0.3327864 |
0.33646468 |
|
0.1927468 |
0.3177662 |
0.3403953 |
0.33990110 |
|
0.2049453 |
0.3208899 |
|
0.33623396 |
|
0.2167602 |
0.3423190 |
|
0.33762308 |
|
0.2058433 |
|
|
0.33762454 |
|
0.1994011 |
|
|
0.33330213 |
|
0.2027731 |
|
|
0.33991445 |
|
0.1963051 |
|
|
0.35101249 |
|
0.2091475 |
|
|
0.34575456 |
|
0.2106636 |
|
|
0.34615514 |
|
0.2093573 |
|
|
0.33388054 |
|
0.2053261 |
|
|
0.33553872 |
|
0.2088231 |
|
|
0.33578366 |
|
0.1983147 |
|
|
0.33838848 |
|
0.1990353 |
|
|
0.34806194 |
|
0.1960416 |
|
|
0.35296958 |
|
0.1956724 |
|
|
0.34350593 |
|
0.2163352 |
|
|
0.33812976 |
|
0.2106004 |
One-way ANOVA
Null hypothesis (Ho): There is no difference in the model means UCOTREC = UGNRWW = UTAGNN = UFLCSP = UGGNN
Alternative hypothesis (H1): At least one model's mean differs from the others
Significance level = 0.05
Summary |
Groups |
Count |
Sum |
Average |
Variance |
COTREC |
34 |
11.48851541 |
0.3378975119 |
0.000009992151219 |
GNRRW |
50 |
17.04070195 |
0.340814039 |
0.00003779439459 |
TAGNN |
25 |
6.406298825 |
0.256251953 |
0.000229300123 |
FLCSP |
50 |
10.15718027 |
0.2031436054 |
0.00008132955373 |
GGNN |
35 |
11.29520972 |
0.3227202778 |
0.00008863380708 |
ANOVA |
|
|
|
|
|
|
Source of Variation |
SS |
df |
MS |
F-value |
P-value |
F(critical) |
Between Groups |
0.650167345 |
4 |
0.1625418362 |
2092.16244 |
0 |
2.419440031 |
Within Groups |
0.01468356685 |
189 |
0.0000776908299 |
Total |
0.6648509118 |
193 |
The F-value and critical F- value are 2092.162 and 2.4194, respectively. The F-value is greater than the critical F-value, therefore, we reject the Ho.
The main purpose of the ANOVA test is to observe the variability between the groups/compared models. However, it does not explain about the magnitude of variability.
Therefore, we use the effect size (η) to know the magnitude of variability between the models. The effect size uses the following table to explain the level of variability.
η |
Size |
0.01 |
small |
0.09 |
medium |
0.25 |
large |
Note: if less than .01, no effect is reported |
η = 0.650167344986137 / 0.664850911836957
η = 0.9779
Here we observe the large effect size between the GNN models.
References:
- https://open.maricopa.edu/psy230mm/chapter/chapter-14-analysis-of-variance/
- https://en.wikipedia.org/wiki/Analysis_of_variance