cl.estimate_cate_by_2_models() does not work with XGBoost version 1.0.2 about causallift HOT 4 CLOSED

The error seems to reproduce using scikit-learn 0.22 or later.
Could you try XGBoost 1.x with scikit-learn 0.21.3?

xgboost 1.0.1 did not reproduce the error with scikit-learn 0.21.3 in my environment.

from causallift.

Indeed, no error with sklearn 0.21.3 and an error with 0.22 or later!

from causallift.

The entire error:
`---------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
in
----> 1 train_df, test_df = cl.estimate_cate_by_2_models()

~/PycharmProjects/bace/venv/lib/python3.6/site-packages/causallift/causal_lift.py in estimate_cate_by_2_models(self)
639
640 if self.runner:
--> 641 self.kedro_context.run(tags=["311_fit", "312_bundle_2_models"])
642 self.uplift_models_dict = self.kedro_context.catalog.load(
643 "uplift_models_dict"

~/PycharmProjects/bace/venv/lib/python3.6/site-packages/causallift/context/flexible_context.py in run(self, tags, runner, node_names, only_missing)
177 )
178 return super().run(
--> 179 tags=tags, runner=runner, node_names=node_names, only_missing=only_missing
180 )

~/PycharmProjects/bace/venv/lib/python3.6/site-packages/causallift/context/flexible_context.py in run(self, **kwargs)
139 ):
140 # type: (...) -> Dict[str, Any]
--> 141 d = super().run(**kwargs)
142 self.catalog.add_feed_dict(d, replace=True)
143 return d

~/PycharmProjects/bace/venv/lib/python3.6/site-packages/causallift/context/flexible_context.py in run(self, runner, **kwargs)
129 ParallelRunner() if runner == "ParallelRunner" else SequentialRunner()
130 )
--> 131 return super().run(runner=runner, **kwargs)
132
133

~/PycharmProjects/bace/venv/lib/python3.6/site-packages/causallift/context/flexible_context.py in run(self, tags, runner, node_names, only_missing)
104 if only_missing and _skippable(self.catalog):
105 return runner.run_only_missing(pipeline, self.catalog)
--> 106 return runner.run(pipeline, self.catalog)
107
108

~/PycharmProjects/bace/venv/lib/python3.6/site-packages/kedro/runner/runner.py in run(self, pipeline, catalog)
80 catalog.add(ds_name, self.create_default_data_set(ds_name))
81
---> 82 self._run(pipeline, catalog)
83
84 self._logger.info("Pipeline execution completed successfully.")

~/PycharmProjects/bace/venv/lib/python3.6/site-packages/kedro/runner/sequential_runner.py in _run(self, pipeline, catalog)
75 for exec_index, node in enumerate(nodes):
76 try:
---> 77 run_node(node, catalog)
78 done_nodes.add(node)
79 except Exception:

~/PycharmProjects/bace/venv/lib/python3.6/site-packages/kedro/runner/runner.py in run_node(node, catalog)
182 """
183 inputs = {name: catalog.load(name) for name in node.inputs}
--> 184 outputs = node.run(inputs)
185 for name, data in outputs.items():
186 catalog.save(name, data)

~/PycharmProjects/bace/venv/lib/python3.6/site-packages/kedro/pipeline/node.py in run(self, inputs)
420 except Exception as exc:
421 self._logger.error("Node %s failed with error: \n%s", str(self), str(exc))
--> 422 raise exc
423
424 def _run_with_no_inputs(self, inputs: Dict[str, Any]):

~/PycharmProjects/bace/venv/lib/python3.6/site-packages/kedro/pipeline/node.py in run(self, inputs)
411 outputs = self._run_with_one_input(inputs, self._inputs)
412 elif isinstance(self._inputs, list):
--> 413 outputs = self._run_with_list(inputs, self._inputs)
414 elif isinstance(self._inputs, dict):
415 outputs = self._run_with_dict(inputs, self._inputs)

~/PycharmProjects/bace/venv/lib/python3.6/site-packages/kedro/pipeline/node.py in _run_with_list(self, inputs, node_inputs)
458 )
459 # Ensure the function gets the inputs in the correct order
--> 460 return self._decorated_func(*[inputs[item] for item in node_inputs])
461
462 def _run_with_dict(self, inputs: Dict[str, Any], node_inputs: Dict[str, str]):

~/PycharmProjects/bace/venv/lib/python3.6/site-packages/causallift/nodes/model_for_each.py in model_for_untreated_fit(*posargs, **kwargs)
250
251 def model_for_untreated_fit(*posargs, **kwargs):
--> 252 return ModelForUntreated().fit(*posargs, **kwargs)
253
254

~/PycharmProjects/bace/venv/lib/python3.6/site-packages/causallift/nodes/model_for_each.py in fit(self, args, df_)
62
63 else:
---> 64 model.fit(X_train, y_train)
65
66 best_estimator = (

~/PycharmProjects/bace/venv/lib/python3.6/site-packages/sklearn/model_selection/search.py in fit(self, X, y, groups, **fit_params)
734 # of the params are estimators as well.
735 self.best_estimator = clone(clone(base_estimator).set_params(
--> 736 **self.best_params_))
737 refit_start_time = time.time()
738 if y is not None:

~/PycharmProjects/bace/venv/lib/python3.6/site-packages/sklearn/base.py in clone(estimator, safe)
80 raise RuntimeError('Cannot clone object %s, as the constructor '
81 'either does not set or modifies parameter %s' %
---> 82 (estimator, name))
83 return new_object
84

RuntimeError: Cannot clone object XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,
colsample_bynode=None, colsample_bytree=1, gamma=0, gpu_id=None,
importance_type='gain', interaction_constraints=None,
learning_rate=0.1, max_delta_step=0, max_depth=3,
min_child_weight=1, missing=None, monotone_constraints=None,
n_estimators=100, n_jobs=-1, nthread=None, num_parallel_tree=None,
objective='binary:logistic', random_state=0, reg_alpha=0,
reg_lambda=1, scale_pos_weight=1, subsample=1, tree_method=None,
validate_parameters=False, verbose=0, verbosity=None), as the constructor either does not set or modifies parameter missing`

from causallift.

Indeed, no error with sklearn 0.21.3 and an error with 0.22 or later!

Great!

I'm afraid that, at this moment, I do not plan to fix the issue with scikit-learn 0.22 because I'm not sure how to fix it and I haven't found any new features of scikit-learn 0.22 useful for CausalLift.
Pull requests are welcome though.

from causallift.