use RandomizedSearchCV and estmator is RandomForestClassifier have bug?

run code is about:

print(__doc__)

import numpy as np

from time import time
from scipy.stats import randint as sp_randint

# from sklearn.model_selection import GridSearchCV
# from sklearn.model_selection import RandomizedSearchCV
from dask_searchcv import GridSearchCV
from dask_searchcv import RandomizedSearchCV
from sklearn.datasets import load_digits
from sklearn.ensemble import RandomForestClassifier

# get some data
digits = load_digits()
X, y = digits.data, digits.target

# build a classifier
clf = RandomForestClassifier(n_estimators=20)


# Utility function to report best scores
def report(results, n_top=3):
    for i in range(1, n_top + 1):
        candidates = np.flatnonzero(results['rank_test_score'] == i)
        for candidate in candidates:
            print("Model with rank: {0}".format(i))
            print("Mean validation score: {0:.3f} (std: {1:.3f})".format(
                results['mean_test_score'][candidate],
                results['std_test_score'][candidate]))
            print("Parameters: {0}".format(results['params'][candidate]))
            print("")


# specify parameters and distributions to sample from
param_dist = {"max_depth": [3, None],
              "max_features": sp_randint(1, 11),
              "min_samples_split": sp_randint(2, 11),
              "min_samples_leaf": sp_randint(1, 11),
              "bootstrap": [True, False],
              "criterion": ["gini", "entropy"]}

# run randomized search
n_iter_search = 20
random_search = RandomizedSearchCV(clf, param_distributions=param_dist,
                                   n_iter=n_iter_search)

start = time()
random_search.fit(X, y)
print("RandomizedSearchCV took %.2f seconds for %d candidates"
      " parameter settings." % ((time() - start), n_iter_search))
report(random_search.cv_results_)

# use a full grid over all parameters
param_grid = {"max_depth": [3, None],
              "max_features": [1, 3, 10],
              "min_samples_split": [2, 3, 10],
              "min_samples_leaf": [1, 3, 10],
              "bootstrap": [True, False],
              "criterion": ["gini", "entropy"]}

# run grid search
grid_search = GridSearchCV(clf, param_grid=param_grid)
start = time()
grid_search.fit(X, y)

print("GridSearchCV took %.2f seconds for %d candidate parameter settings."
      % (time() - start, len(grid_search.cv_results_['params'])))
report(grid_search.cv_results_)

the error is :

Traceback (most recent call last):
  File "/root/anaconda3/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2862, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-139-ecec65d20380>", line 50, in <module>
    random_search.fit(X, y)
  File "/root/anaconda3/lib/python3.6/site-packages/dask_searchcv/model_selection.py", line 867, in fit
    out = scheduler(dsk, keys, num_workers=n_jobs)
  File "/root/anaconda3/lib/python3.6/site-packages/dask/threaded.py", line 75, in get
    pack_exception=pack_exception, **kwargs)
  File "/root/anaconda3/lib/python3.6/site-packages/dask/local.py", line 521, in get_async
    raise_exception(exc, tb)
  File "/root/anaconda3/lib/python3.6/site-packages/dask/compatibility.py", line 60, in reraise
    raise exc
File "/root/anaconda3/lib/python3.6/site-packages/dask/local.py", line 290, in execute_task
    result = _execute_task(task, data)
  File "/root/anaconda3/lib/python3.6/site-packages/dask/local.py", line 271, in _execute_task
    return func(*args2)
  File "/root/anaconda3/lib/python3.6/site-packages/dask_searchcv/methods.py", line 280, in fit_and_score
    fields, params, fit_params)
  File "/root/anaconda3/lib/python3.6/site-packages/dask_searchcv/methods.py", line 216, in fit
    est.fit(X, y, **fit_params)
  File "/root/anaconda3/lib/python3.6/site-packages/sklearn/ensemble/forest.py", line 316, in fit
    random_state=random_state)
  File "/root/anaconda3/lib/python3.6/site-packages/sklearn/ensemble/base.py", line 125, in _make_estimator
    estimator = clone(self.base_estimator_)
  File "/root/anaconda3/lib/python3.6/site-packages/sklearn/base.py", line 60, in clone
    new_object_params = estimator.get_params(deep=False)
  File "/root/anaconda3/lib/python3.6/site-packages/sklearn/base.py", line 241, in get_params
    warnings.filters.pop(0)
IndexError: pop from empty list

[TomAugspurger]

Probably not. I think that 0.20 is reasonably close, and scikit-learn doesn’t really have enough development resources to maintain backport branches.

[wtbarnes]

Ok I can confirm that the above example with GridSearchCV works if I use scikit-learn 0.20.dev, i.e. the master branch. Is it worth creating an issue in scikit-learn to ask for a backport of this fix to 0.19?