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[SeasonalNaive]
action_files/test_efficiency.py+1%
116 µs114.8 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[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[HistoricAverage]
action_files/test_efficiency.py0%
119.8 µs119.6 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[OptimizedTheta]
action_files/test_efficiency.py0%
5.4 ms5.4 ms
test_efficiency[DynamicTheta]
action_files/test_efficiency.py0%
4.8 ms4.8 ms
test_efficiency[ConstantModel]
action_files/test_efficiency.py0%
59.6 µs59.6 µs
test_efficiency[RandomWalkWithDrift]
action_files/test_efficiency.py0%
94.6 µs94.6 µs
test_efficiency[HoltWinters]
action_files/test_efficiency.py0%
280.5 ms280.4 ms
test_efficiency[GARCH]
action_files/test_efficiency.py0%
22.3 ms22.3 ms
test_efficiency[MSTL]
action_files/test_efficiency.py0%
1.1 s1.1 s
test_efficiency[SimpleExponentialSmoothingOptimized]
action_files/test_efficiency.py0%
138 µs138 µs
test_efficiency[ARCH]
action_files/test_efficiency.py0%
20.5 ms20.5 ms
test_efficiency[ADIDA]
action_files/test_efficiency.py0%
295 µs295 µs
test_efficiency[MFLES]
action_files/test_efficiency.py0%
7.9 ms7.9 ms
test_efficiency[Theta]
action_files/test_efficiency.py0%
4.8 ms4.8 ms
test_efficiency[AutoMFLES]
action_files/test_efficiency.py0%
132.5 ms132.5 ms
test_efficiency[Naive]
action_files/test_efficiency.py0%
65 µs65 µs
test_efficiency[AutoARIMA]
action_files/test_efficiency.py0%
18 ms18 ms
test_efficiency[AutoTBATS]
action_files/test_efficiency.py0%
8.6 s8.6 s
test_efficiency[SimpleExponentialSmoothing]
action_files/test_efficiency.py0%
91.4 µs91.5 µs
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
9 days ago
by yoselalberto+0.05%
add uv.lock
8512a30
4 days ago
by yoselalberto