Error message with LinearDML
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Description
The following estimation works fine:
est = LinearDML(model_y = LinearRegression()
, model_t = LogisticRegression()
, discrete_treatment = True, random_state = 123)
est.fit(y, T, X=None, W = W)
However if I don't specify the first stage models:
est = LinearDML(discrete_treatment = True, random_state = 123)
est.fit(y, T, X=None, W = W)
I get the following error message:
ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 2 dimensions. The detected shape was (3, 10) + inhomogeneous part.
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Research direction
Start by reproducing the two LinearDML snippets from the issue, comparing the explicit first-stage models with the default-model path. Trace the LinearDML entry point and its default model setup; done means fitting with omitted models completes without the reported ValueError and remains consistent with the explicit-model case.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, scikit-learn
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 45/100