Error when launching xgboost

[mattvan83]

Hi @raamana ,

I got an error when trying to launch both multi-class or binary classifications using xgboost:

multiprocessing.pool.RemoteTraceback: 
"""
Traceback (most recent call last):
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/multiprocessing/pool.py", line 121, in worker
    result = (True, func(*args, **kwds))
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/multiprocessing/pool.py", line 44, in mapstar
    return list(map(*args))
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/site-packages/neuropredict/rhst.py", line 624, in holdout_trial_compare_datasets
    feat_select_method=feat_select_method)
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/site-packages/neuropredict/rhst.py", line 102, in eval_optimized_model_on_testset
    param_grid, train_perc)
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/site-packages/neuropredict/rhst.py", line 194, in optimize_pipeline_via_grid_search_CV
    gs.fit(train_data_mat, train_labels)
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/site-packages/sklearn/model_selection/_search.py", line 688, in fit
    self._run_search(evaluate_candidates)
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/site-packages/sklearn/model_selection/_search.py", line 1149, in _run_search
    evaluate_candidates(ParameterGrid(self.param_grid))
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/site-packages/sklearn/model_selection/_search.py", line 667, in evaluate_candidates
    cv.split(X, y, groups)))
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/site-packages/joblib/parallel.py", line 1003, in __call__
    if self.dispatch_one_batch(iterator):
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/site-packages/joblib/parallel.py", line 834, in dispatch_one_batch
    self._dispatch(tasks)
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/site-packages/joblib/parallel.py", line 753, in _dispatch
    job = self._backend.apply_async(batch, callback=cb)
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/site-packages/joblib/_parallel_backends.py", line 201, in apply_async
    result = ImmediateResult(func)
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/site-packages/joblib/_parallel_backends.py", line 582, in __init__
    self.results = batch()
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/site-packages/joblib/parallel.py", line 256, in __call__
    for func, args, kwargs in self.items]
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/site-packages/joblib/parallel.py", line 256, in <listcomp>
    for func, args, kwargs in self.items]
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/site-packages/sklearn/model_selection/_validation.py", line 516, in _fit_and_score
    estimator.fit(X_train, y_train, **fit_params)
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/site-packages/sklearn/pipeline.py", line 356, in fit
    self._final_estimator.fit(Xt, y, **fit_params)
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/site-packages/xgboost/sklearn.py", line 732, in fit
    callbacks=callbacks)
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/site-packages/xgboost/training.py", line 216, in train
    xgb_model=xgb_model, callbacks=callbacks)
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/site-packages/xgboost/training.py", line 74, in _train_internal
    bst.update(dtrain, i, obj)
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/site-packages/xgboost/core.py", line 1109, in update
    dtrain.handle))
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/site-packages/xgboost/core.py", line 176, in _check_call
    raise XGBoostError(py_str(_LIB.XGBGetLastError()))
xgboost.core.XGBoostError: Invalid Parameter format for num_feature expect int (non-negative) but value='sqrt'
"""

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/bin/neuropredict", line 8, in <module>
    sys.exit(main())
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/site-packages/neuropredict/__main__.py", line 11, in main
    run_workflow.cli()
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/site-packages/neuropredict/run_workflow.py", line 976, in cli
    grid_search_level, classifier, feat_select_method)
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/site-packages/neuropredict/run_workflow.py", line 951, in prepare_and_run
    options_path=options_path)
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/site-packages/neuropredict/rhst.py", line 382, in run
    cv_results = pool.map(partial_func_holdout, range(num_repetitions))
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/multiprocessing/pool.py", line 268, in map
    return self._map_async(func, iterable, mapstar, chunksize).get()
  File "/homes_unix/mvanhoutte/Soft/anaconda3/envs/neuropredict/lib/python3.7/multiprocessing/pool.py", line 657, in get
    raise self._value
xgboost.core.XGBoostError: Invalid Parameter format for num_feature expect int (non-negative) but value='sqrt'

Could you help me with this?

[raamana]

I know this is an issue - I will work on this during the brainhack global