Fix/969 MSTL cross validation with refit = False
#1100Comparing
yoselalberto:fix/969_MSTL_cross_validation
(8512a30
) withmain
(a0ef3f4
)0%
- Untouched
- 38
Benchmarks
38 total
test_efficiency[CrostonOptimized]
action_files/test_efficiency.py-2%
298.2 µs304.6 µs
test_efficiency[AutoTheta]
action_files/test_efficiency.py-2%
14.2 ms14.4 ms
test_efficiency[SeasonalNaive]
action_files/test_efficiency.py+1%
116 µs114.8 µs
test_efficiency[IMAPA]
action_files/test_efficiency.py-1%
334.6 µs337.2 µs
test_efficiency[CrostonSBA]
action_files/test_efficiency.py-1%
219.1 µs220.7 µs
test_efficiency[SeasonalWindowAverage]
action_files/test_efficiency.py+1%
155.3 µs154.4 µs
test_efficiency[AutoCES]
action_files/test_efficiency.py+1%
3 ms3 ms
test_efficiency[TSB]
action_files/test_efficiency.py-1%
156.9 µs157.8 µs
test_efficiency[TBATS]
action_files/test_efficiency.py0%
209.7 ms210.6 ms
test_efficiency[SeasonalExponentialSmoothingOptimized]
action_files/test_efficiency.py0%
480.7 µs478.8 µs
test_efficiency[SeasonalExponentialSmoothing]
action_files/test_efficiency.py0%
368.4 µs367 µs
test_efficiency[ZeroModel]
action_files/test_efficiency.py0%
57.9 µs58.1 µs
test_efficiency[CrostonClassic]
action_files/test_efficiency.py0%
215.9 µs216.5 µs
test_efficiency[AutoETS]
action_files/test_efficiency.py0%
409.8 ms410.8 ms
test_efficiency[Holt]
action_files/test_efficiency.py0%
18 ms18 ms
test_efficiency[HistoricAverage]
action_files/test_efficiency.py0%
119.8 µs119.6 µs
test_efficiency[NaNModel]
action_files/test_efficiency.py0%
57.3 µs57.4 µs
test_efficiency[WindowAverage]
action_files/test_efficiency.py0%
124.3 µs124.5 µs
test_efficiency[ARIMA]
action_files/test_efficiency.py0%
3.9 ms3.9 ms
test_efficiency[SimpleExponentialSmoothing]
action_files/test_efficiency.py0%
91.4 µs91.5 µs
test_efficiency[AutoRegressive]
action_files/test_efficiency.py0%
155.2 ms155 ms
test_efficiency[DynamicOptimizedTheta]
action_files/test_efficiency.py0%
5.4 ms5.4 ms
test_efficiency[AutoTBATS]
action_files/test_efficiency.py0%
8.6 s8.6 s
test_efficiency[OptimizedTheta]
action_files/test_efficiency.py0%
5.4 ms5.4 ms
test_efficiency[DynamicTheta]
action_files/test_efficiency.py0%
4.8 ms4.8 ms
Commits
Click on a commit to change the comparison rangeBase
main
a0ef3f4
-0.16%
switch to numpy-based metrics, utilsforecast.losses expects dataframes (values are numpy.ndarray's), add instruction regarding how to run the m3 test locally CI-style
d7cc2b1
5 months ago
by yoselalberto+0.05%
add uv.lock
8512a30
5 months ago
by yoselalberto