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[BUG] Fix arguments dropped or misapplied in the classifier and regressor getters #550

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Merged
MatthewMiddlehurst merged 3 commits into from
Oct 17, 2026
Merged

[BUG] Fix arguments dropped or misapplied in the classifier and regressor getters #550

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bd57ae0
[BUG] Fix arguments dropped or misapplied in classifier and regressor…
MatthewMiddlehurst Oct 13, 2026
396c253
Remove getter tests and keep drcif-unequal as it was
MatthewMiddlehurst Oct 13, 2026
a92ec06
Pass fit_contract to the interval forest classifiers and regressors
MatthewMiddlehurst Oct 13, 2026
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13 changes: 11 additions & 2 deletions tsml_eval/experiments/_get_classifier.py
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Original file line number Diff line number Diff line change
Expand Up @@ -491,6 +491,7 @@ def _set_classifier_distance_based(
estimator=KNeighborsTimeSeriesClassifier(),
param_grid=param_grid,
scoring="accuracy",
n_jobs=n_jobs,
**kwargs,
)
elif c == "grailclassifier" or c == "grail":
Expand Down Expand Up @@ -639,6 +640,7 @@ def _set_classifier_interval_based(
n_estimators=500,
random_state=random_state,
n_jobs=n_jobs,
time_limit_in_minutes=fit_contract,
**kwargs,
)
elif c == "randomintervalspectralensembleclassifier" or c == "rise":
Expand All @@ -649,6 +651,7 @@ def _set_classifier_interval_based(
return RandomIntervalSpectralEnsembleClassifier(
random_state=random_state,
n_jobs=n_jobs,
time_limit_in_minutes=fit_contract,
**kwargs,
)
elif c == "tsf-500":
Expand All @@ -658,6 +661,7 @@ def _set_classifier_interval_based(
n_estimators=500,
random_state=random_state,
n_jobs=n_jobs,
time_limit_in_minutes=fit_contract,
**kwargs,
)
elif c == "timeseriesforestclassifier" or c == "tsf":
Expand All @@ -666,6 +670,7 @@ def _set_classifier_interval_based(
return TimeSeriesForestClassifier(
random_state=random_state,
n_jobs=n_jobs,
time_limit_in_minutes=fit_contract,
**kwargs,
)
elif c == "cif-500":
Expand All @@ -675,6 +680,7 @@ def _set_classifier_interval_based(
n_estimators=500,
random_state=random_state,
n_jobs=n_jobs,
time_limit_in_minutes=fit_contract,
**kwargs,
)
elif c == "canonicalintervalforestclassifier" or c == "cif":
Expand All @@ -683,6 +689,7 @@ def _set_classifier_interval_based(
return CanonicalIntervalForestClassifier(
random_state=random_state,
n_jobs=n_jobs,
time_limit_in_minutes=fit_contract,
**kwargs,
)
elif c == "stsf-500":
Expand All @@ -692,6 +699,7 @@ def _set_classifier_interval_based(
n_estimators=500,
random_state=random_state,
n_jobs=n_jobs,
time_limit_in_minutes=fit_contract,
**kwargs,
)
elif c == "supervisedtimeseriesforest" or c == "stsf":
Expand All @@ -700,6 +708,7 @@ def _set_classifier_interval_based(
return SupervisedTimeSeriesForest(
random_state=random_state,
n_jobs=n_jobs,
time_limit_in_minutes=fit_contract,
**kwargs,
)
elif c == "drcif-500":
Expand Down Expand Up @@ -887,7 +896,7 @@ def _set_classifier_shapelet_based(
elif c == "rdstclassifier" or c == "rdst":
from aeon.classification.shapelet_based import RDSTClassifier

return RDSTClassifier(random_state=random_state, **kwargs)
return RDSTClassifier(random_state=random_state, n_jobs=n_jobs, **kwargs)
elif (
c == "randomshapeletforestclassifier"
or c == "randomshapeletforest"
Expand Down Expand Up @@ -927,7 +936,7 @@ def _set_classifier_vector(c, random_state, n_jobs, fit_contract, checkpoint, kw
elif c == "logisticregression" or c == "logistic":
from sklearn.linear_model import LogisticRegression

return LogisticRegression(random_state=random_state, n_jobs=n_jobs, **kwargs)
return LogisticRegression(random_state=random_state, **kwargs)
elif c == "prevalidatedridgeclassifier" or c == "prevalidatedridge":
from aeon.classification.sklearn import PrevalidatedRidgeClassifier

Expand Down
26 changes: 22 additions & 4 deletions tsml_eval/experiments/_get_regressor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -269,22 +269,30 @@ def _set_regressor_distance_based(
if r == "1nn-ed":
from aeon.regression.distance_based import KNeighborsTimeSeriesRegressor

return KNeighborsTimeSeriesRegressor(**kwargs)
return KNeighborsTimeSeriesRegressor(
distance="euclidean", n_jobs=n_jobs, **kwargs
)
elif r == "5nn-ed":
from aeon.regression.distance_based import KNeighborsTimeSeriesRegressor

return KNeighborsTimeSeriesRegressor(n_neighbors=5, **kwargs)
return KNeighborsTimeSeriesRegressor(
n_neighbors=5, distance="euclidean", n_jobs=n_jobs, **kwargs
)
elif r == "kneighborstimeseriesregressor" or r == "1nn-dtw":
from aeon.regression.distance_based import KNeighborsTimeSeriesRegressor

return KNeighborsTimeSeriesRegressor(
distance="dtw", distance_params={"window": 0.1}, **kwargs
distance="dtw", distance_params={"window": 0.1}, n_jobs=n_jobs, **kwargs
)
elif r == "5nn-dtw":
from aeon.regression.distance_based import KNeighborsTimeSeriesRegressor

return KNeighborsTimeSeriesRegressor(
n_neighbors=5, distance="dtw", distance_params={"window": 0.1}, **kwargs
n_neighbors=5,
distance="dtw",
distance_params={"window": 0.1},
n_jobs=n_jobs,
**kwargs,
)
elif r == "1nn-msm":
from aeon.regression.distance_based import KNeighborsTimeSeriesRegressor
Expand All @@ -293,6 +301,8 @@ def _set_regressor_distance_based(
n_neighbors=1,
distance="msm",
distance_params={"window": None, "independent": True, "c": 1},
n_jobs=n_jobs,
**kwargs,
)
elif r == "5nn-msm":
from aeon.regression.distance_based import KNeighborsTimeSeriesRegressor
Expand All @@ -301,6 +311,8 @@ def _set_regressor_distance_based(
n_neighbors=5,
distance="msm",
distance_params={"window": None, "independent": True, "c": 1},
n_jobs=n_jobs,
**kwargs,
)


Expand Down Expand Up @@ -397,6 +409,7 @@ def _set_regressor_interval_based(
return TimeSeriesForestRegressor(
random_state=random_state,
n_jobs=n_jobs,
time_limit_in_minutes=fit_contract,
**kwargs,
)
elif r == "tsf-i":
Expand All @@ -422,6 +435,7 @@ def _set_regressor_interval_based(
n_estimators=500,
random_state=random_state,
n_jobs=n_jobs,
time_limit_in_minutes=fit_contract,
**kwargs,
)
elif r == "rise-500":
Expand All @@ -433,6 +447,7 @@ def _set_regressor_interval_based(
n_estimators=500,
random_state=random_state,
n_jobs=n_jobs,
time_limit_in_minutes=fit_contract,
**kwargs,
)
elif r == "randomintervalspectralensembleregressor" or r == "rise":
Expand All @@ -443,6 +458,7 @@ def _set_regressor_interval_based(
return RandomIntervalSpectralEnsembleRegressor(
random_state=random_state,
n_jobs=n_jobs,
time_limit_in_minutes=fit_contract,
**kwargs,
)
elif r == "cif-500":
Expand All @@ -452,6 +468,7 @@ def _set_regressor_interval_based(
n_estimators=500,
random_state=random_state,
n_jobs=n_jobs,
time_limit_in_minutes=fit_contract,
**kwargs,
)
elif r == "canonicalintervalforestregressor" or r == "cif":
Expand All @@ -460,6 +477,7 @@ def _set_regressor_interval_based(
return CanonicalIntervalForestRegressor(
random_state=random_state,
n_jobs=n_jobs,
time_limit_in_minutes=fit_contract,
**kwargs,
)
elif r == "drcif" or r == "drcifregressor":
Expand Down
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